Private data sharing method and device and electronic equipment

Abstract

The invention discloses a private data sharing method and device and electronic equipment, and belongs to the technical field of data processing. The method comprises the following steps: acquiring user interaction information of a first user and a second user; determining a first score of the first user to the second user and a second score of the second user to the first user according to the user interaction information; and adjusting the sharing range of the private data between the first user and the second user according to the first score and the second score.

Description

Technical Field

[0001] This application belongs to the field of data processing technology, and specifically relates to a method, apparatus and electronic device for sharing privacy data. Background Technology

[0002] In modern online social scenarios, user recommendations and online status management are core functions for achieving efficient social interaction and privacy protection. Current implementation methods mainly include the following:

[0003] The first type is a static interest tag matching mechanism, which recommends potential friends based on the similarity of predefined tags by having users manually input interest tags. The second type is a recommendation mechanism based on specific behavioral profiles, which focuses on analyzing single-dimensional behavioral data such as user browsing history, likes, and purchase history, and generates recommendations through quantitative evaluation. The third type is a blacklist / whitelist online status control mechanism, which relies on users to manually add specific individuals to a list to show or hide their online status.

[0004] While current implementation methods can achieve basic social functions in specific scenarios, they are difficult to adapt to the dynamic changes in social trust relationships. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, and electronic device for sharing privacy data, which can solve the problem of difficulty in adapting to dynamic changes in social trust relationships.

[0006] In a first aspect, embodiments of this application provide a method for sharing privacy data, the method comprising:

[0007] Obtain user interaction information between the first user and the second user;

[0008] Based on user interaction information, determine the first user's first rating of the second user and the second user's second rating of the first user;

[0009] Based on the first and second ratings, the scope of privacy data sharing between the first and second users will be adjusted.

[0010] Secondly, embodiments of this application provide a privacy data sharing device, the device comprising:

[0011] The acquisition module is used to acquire user interaction information between the first user and the second user.

[0012] The determination module is used to determine, based on user interaction information, the first user's first rating of the second user and the second user's second rating of the first user;

[0013] The adjustment module is used to adjust the scope of privacy data sharing between the first user and the second user based on the first rating and the second rating.

[0014] Thirdly, embodiments of this application provide an electronic device including a processor and a memory, wherein the memory stores programs or instructions executable on the processor, and the programs or instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0015] Fourthly, embodiments of this application provide a readable storage medium on which a program or instructions are stored, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0016] Fifthly, embodiments of this application provide a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the method as described in the first aspect.

[0017] In a sixth aspect, embodiments of this application provide a computer program product stored in a storage medium, which is executed by at least one processor to implement the method described in the first aspect.

[0018] In the embodiments of this application, by acquiring user interaction information of the first user and the second user in various social scenarios, the relationship between users can be reflected truthfully and comprehensively, laying a solid foundation for accurate analysis of user relationships. Based on the user interaction information, a first rating of the first user to the second user and a second rating of the second user to the first user are determined. The first and second ratings are updated continuously as user interaction behavior occurs, enabling timely capture of changes in user relationships. Based on the first and second ratings, the evaluation of each other by the first user and the second user can be comprehensively considered, adjusting the scope of privacy data sharing between the first user and the second user, improving the flexibility and real-time nature of privacy sharing, and realizing refined management of privacy data. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a method for sharing privacy data provided in an embodiment of this application;

[0020] Figure 2a This is a schematic diagram of a privacy data interface provided in an embodiment of this application;

[0021] Figure 2b This is a schematic diagram of interactive animation information and scoring progress information provided in an embodiment of this application;

[0022] Figure 2cThis is a schematic diagram of a first animation and a second animation provided in an embodiment of this application;

[0023] Figure 3 This is a schematic diagram illustrating enterprise identification information and dynamic matching information provided in an embodiment of this application;

[0024] Figure 4 This is a structural diagram of a privacy data sharing device provided in an embodiment of this application;

[0025] Figure 5 This is one of the hardware structure diagrams of the electronic device according to an embodiment of this application;

[0026] Figure 6 This is the second schematic diagram of the hardware structure of the electronic device according to an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0028] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0029] In response to the problems in related technologies, embodiments of this application provide a method, apparatus, and electronic device for sharing privacy data, which can solve the problem of difficulty in adapting to the dynamic changes in social trust relationships in related technologies.

[0030] The method for sharing privacy data provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0031] Figure 1 A flowchart illustrating a method for sharing privacy data as provided in this application embodiment.

[0032] like Figure 1As shown, the method for sharing privacy data may include steps 110-130. This method is applied to a privacy data sharing device, as detailed below:

[0033] Step 110: Obtain user interaction information of the first user and the second user in various social scenarios;

[0034] Social scenarios refer to various environments in which users interact socially, such as chatting, group discussions, sharing updates, and participating in joint activities. User interaction information records data on user interaction behaviors generated in social scenarios, including chat frequency, message reply timeliness, liking behavior data, commenting behavior data, and the number of times they participate in joint social activities.

[0035] By collecting the interaction behavior of the first and second users in real time, these behaviors are transformed into structured user interaction information, providing a data foundation for subsequent rating calculations.

[0036] Step 120: Based on user interaction information, determine the first user's first rating of the second user and the second user's second rating of the first user;

[0037] The first and second ratings are numerical indicators calculated using specific algorithms based on user interaction information, used to quantify the level of trust or the closeness of relationships between users.

[0038] Analyze user interaction information. For example, frequent and high-quality interactions will improve the rating, while prolonged periods of no interaction or negative interaction will lower the rating, thus deriving a first and second rating that reflects the level of trust between the two parties.

[0039] Step 130: Adjust the scope of privacy data sharing between the first user and the second user based on the first score and the second score.

[0040] Privacy data refers to data set by users in social media that includes sensitive personal information and private updates that require access control.

[0041] Based on the first and second ratings, the scope of privacy data sharing between the first and second users can be dynamically adjusted to achieve dynamic privacy data access control.

[0042] Therefore, by analyzing user interactions in social scenarios to determine ratings and controlling the scope of privacy data sharing based on these ratings, changes in trust relationships between users can be dynamically reflected, enabling fine-grained privacy permission management. The system can automatically update ratings and adjust sharing scope based on changes in user interactions, avoiding the rigidity of static privacy settings and improving the flexibility and real-time nature of privacy management.

[0043] For example, in the metaverse social network, user interaction information of the first and second users in various social scenarios is obtained. In the social scenario of the virtual workplace, user interaction information includes the content of speeches in virtual meetings and the completion status of tasks in project collaborations; in the social scenario of virtual events, user interaction information includes comments on virtual exhibits and interactive behaviors in virtual concerts; in the social scenario of virtual communities, user interaction information includes post topics, reply frequency, etc. By comprehensively collecting interaction information from multiple scenarios, a rich and realistic data foundation is provided for subsequent analysis.

[0044] First and second ratings are determined based on user interaction information. In virtual events, users who frequently exchange insights about exhibits and actively participate in interactive activities also receive positive feedback. This rating mechanism quantifies user interaction behavior in different scenarios, dynamically reflecting the closeness of relationships and trust levels between users. Compared to traditional static evaluation methods, it is better suited to the dynamic nature of relationships in metaverse social interactions.

[0045] Based on the first and second ratings, the system displays privacy data corresponding to the first and second ratings, such as details of personal work achievements in the virtual workplace and private activities in the virtual community. This not only protects user privacy and prevents the arbitrary leakage of sensitive information, but also promotes deeper communication among users at appropriate times and drives the development of social relationships.

[0046] By using first and second ratings to accurately assess user relationships, dynamic and hierarchical management of privacy data is achieved, enhancing the user's social experience in the metaverse social network, strengthening the security and effectiveness of social interactions, and improving social efficiency.

[0047] In one possible embodiment, step 130 may specifically include the following steps:

[0048] If both the first score and the second score are greater than or equal to the first threshold, the scope of sharing of privacy data between the first user and the second user is the first sharing scope.

[0049] If both the first and second scores are greater than or equal to the second threshold, the scope of sharing privacy data between the first user and the second user is the second sharing scope.

[0050] The second threshold is greater than the first threshold, and the first shared range at least partially overlaps with the second shared range.

[0051] When both the first score and the second score are determined to be greater than or equal to the first threshold, for example, the first threshold is set to 0.6, a basic first sharing range will be set for the sharing of privacy data between the first user and the second user. The first sharing range usually includes basic non-sensitive information.

[0052] When both parties' ratings reach the second threshold, for example, if the second threshold is set to 0.9, a second sharing scope will be activated. The second sharing scope includes more detailed personal data or historical data. The second threshold is greater than the first threshold, and there is at least partial overlap between the first and second sharing scopes, thus establishing a clear grading standard.

[0053] For example, in a social networking application, the first sharing scope allows users to view each other's public posts and basic information, such as profile pictures and nicknames. The second sharing scope goes further, allowing users to view the content of private photo albums or precise geolocation information. When both user A's rating of user B and user B's rating of user A increase from 0.85 to 0.95, their sharing scope is automatically upgraded from the first to the second sharing scope, and user B can then access user A's private photo albums. Conversely, if the rating drops back to 0.88, the sharing scope reverts to the first sharing scope, access to private photo albums is revoked, but basic information viewing permissions remain unchanged.

[0054] Thus, the first threshold ensures that basic interactive trust is sufficient to obtain initial data sharing capabilities, while the second threshold corresponds to a high level of trust, authorizing deeper data interaction and realizing refined and automated management of privacy data sharing.

[0055] In one possible embodiment, step 130 may specifically include the following steps:

[0056] If both the first score and the second score are greater than or equal to the first threshold, the first collaboration function between the first user and the second user is enabled, and the privacy data obtained by the first collaboration function is within the first sharing scope.

[0057] If both the first score and the second score are greater than or equal to the second threshold, the second collaboration function between the first user and the second user is enabled, and the privacy data obtained by the second collaboration function is within the second sharing scope.

[0058] The second threshold is greater than the first threshold, and the first shared range at least partially overlaps with the second shared range.

[0059] The system continuously monitors the bidirectional ratings between the first and second users, i.e., the first rating and the second rating, and compares them with a series of increasing thresholds. When both users' ratings reach a certain threshold, the system automatically enables the collaboration function corresponding to that threshold level. For example, when both the first and second ratings exceed the first threshold, the system enables the first collaboration function, which is authorized to access privacy data within the first shared scope.

[0060] When the first and second ratings are further raised to a second threshold, a more powerful second collaboration feature is enabled, which can access private data within the second sharing scope. The second threshold is higher than the first threshold, and the second sharing scope fully covers or at least partially overlaps with the first sharing scope. This ensures that as the trust level increases, users can not only enable new features but also continue to use existing features, and that data access permissions are backward compatible.

[0061] For example, in a project management platform, the first threshold is set to 0.7, corresponding to the first collaborative function of task assignment and progress monitoring, with the first shared scope allowing access to members' work phone numbers and department information. The second threshold is set to 0.9, corresponding to the second collaborative function of joint financial budget approval, with the second shared scope further allowing access to members' salary grade information. When users A and B both reach a mutual rating of 0.75, they can assign tasks to each other and see each other's work phone numbers. As their trust deepens and their mutual rating reaches 0.92, the joint financial approval function will be automatically enabled for them. During this process, this function will allow them to access necessary salary information for decision-making, while basic functions such as task assignment remain available. If the rating drops back to 0.88, the joint approval function and its access to salary data will be disabled, but the task collaboration function and its corresponding basic information access permissions remain unchanged.

[0062] By associating the scope of privacy data sharing with specific collaborative functions and controlling the activation of different levels of functions through preset multi-level scoring thresholds, refined management of data sharing can be achieved, which can smoothly adapt to the development of user relationships.

[0063] The first shared scope is located within the second shared scope.

[0064] The first sharing scope is fully encompassed within the second sharing scope. This means that when a user meets a higher threshold, they will automatically gain access to lower-level privacy data and unlock new data categories, thus forming a progressive data sharing model.

[0065] Based on the comparison results of the two-way scores and preset thresholds, different levels of collaboration functions are dynamically activated. When both the first score and the second score reach the first threshold, the first collaboration function is enabled. This function can only access privacy data within the first sharing scope of the basic layer. When the scores are further improved and both reach a higher second threshold, the second collaboration function is enabled. This function is granted access to a broader second sharing scope, which not only includes all data within the first sharing scope but also introduces more sensitive or in-depth data types.

[0066] Because of the clear inclusion relationships between shared scopes, data permission granting is ensured to be progressive, eliminating the need to handle complex permission overlap issues when upgrading or downgrading a shared scope; simply switching scopes suffices. As the relationship deepens, users can gradually unlock deeper levels of data interaction, which aligns with social norms and enhances users' perception of transparency and fairness in privacy controls. The clear data hierarchy allows for precise management of the data types included in each shared scope, improving the granularity of privacy protection.

[0067] The privacy data included in the first sharing scope includes at least one of the following:

[0068] Personal information; location information; social activity; application usage data.

[0069] Personal information refers to the basic set of data that can directly or indirectly identify a specific user. It includes not only public or semi-public identifiers such as names, nicknames, and profile pictures, but also detailed profile information with privacy attributes. This typically involves privacy level labels, which are tags that classify the sensitivity of different user data fields. For example, an email address might be labeled "Level 3 - Can be shared with friends," while an ID number might be labeled "Level 5 - Absolutely private." In addition, it includes descriptive data such as personal interests, occupational information, and educational background used to build user profiles.

[0070] Location information is a general term for data about a user's geographical location. Its sharing scope can be divided according to precision. Within the first sharing scope, location data is typically shared in a blurred or low-precision manner. For example, it might be a coarse location at the city, region, or street level, used to represent the user's approximate activity range rather than their precise real-time location.

[0071] Social feeds refer to a time-series stream of content updates generated by users within a platform. This includes user-initiated text, images, links, status updates, and records of interactions with other users, such as liking, commenting on, and sharing others' content. Within the first sharing scope, the visibility of these feeds is limited, for example, only displaying a subset of non-sensitive feeds or feeds within a certain time window.

[0072] Application usage data is a type of data that deeply reflects user behavior and habits, going beyond the application list itself and delving into usage details. This includes: recently used applications and their frequency; application usage duration, i.e., statistics on the user's active time on a particular application; application online status, i.e., whether the user is currently in a particular application or within a certain period of time. It also includes the application data itself, i.e., user activity records generated within a specific application, such as chat log summaries or encrypted summaries from instant messaging applications, game battle records from gaming applications, and game achievement markers.

[0073] The first scope of sharing includes basic personal information such as anonymized nicknames and public hobbies, approximate device location information such as city level, and partially public social activity such as unmarked location images.

[0074] In one possible embodiment, the privacy data included in the second sharing scope includes at least one of the following:

[0075] Personal information; location information; social media activity; app usage data; images; videos; files.

[0076] The second sharing scope is defined as a superset based on all data categories in the first sharing scope. It not only fully includes all data items in the first scope but also extends to cover more sensitive and richer multimedia and file data, specifically including images, videos, and files. When the two-way rating between users increases from meeting only the first threshold to meeting a higher second threshold, that is, without losing any original data access rights, the ability to access deeply private content such as images, videos, and files is added.

[0077] The second scope of sharing expands beyond the first scope to include all data, extending to more core privacy data, such as complete personal information including detailed profiles and sensitive interests with privacy level indicators, precise real-time location information, all social activities including content with precise geotags, and in-depth application usage data such as a list of recently used applications, usage time for each application, real-time online status, and even specific application data such as encrypted chat log summaries, game battle records, and special game achievement indicators.

[0078] By explicitly classifying resources such as images, videos, and documents, which often contain highly personal information, into a higher trust level, the protection of core privacy data is greatly strengthened, ensuring that this data is shared only when the relationship is deep enough. This strictly adheres to the security principles of data minimization and purpose limitation.

[0079] The clear data hierarchy ensures a robust access control logic. When performing permission upgrades or downgrades, only a set switch is needed, eliminating the need to handle complex, asymmetric permission combinations, thus reducing implementation complexity and maintenance costs. The smooth permission expansion path, from basic information to multimedia content, intuitively reflects the natural development of interpersonal relationships in real life, from superficial understanding to deep mutual trust, thereby enhancing users' understanding and trust in the privacy control mechanism.

[0080] In one possible embodiment, a first identifier of the second user is displayed on a first user's first terminal. The first identifier is used to indicate that the first score is greater than a first threshold. The first user presets or adjusts the sharing range of the privacy data corresponding to the first identifier to a third sharing range based on the first identifier.

[0081] If both the first user's third rating of the third user and the third user's fourth rating of the first user are greater than the first threshold, the first user shares privacy data with the third user based on the third sharing scope, and the third user shares privacy data with the first user based on the first sharing scope.

[0082] An abstract scoring threshold is linked to an intuitive user interface element—the first identifier—and users are given the ability to fine-tune the privacy policy represented by that identifier. When a first user's first device determines that its initial score for a second user exceeds the first threshold, the first identifier is displayed for the second user in the user interface. This identifier, as a visual symbol, intuitively indicates that the relationship between the two parties has reached a defined baseline trust level. At this point, the first user is granted advanced permissions: through interactive operations, such as clicking the first identifier, they can enter the settings interface to preset or adjust the scope of privacy data sharing associated with this trust level. This user-defined scope is defined as the third sharing scope.

[0083] Custom settings will be recorded and applied as new default rules to all relationships that reach this trust level. When the interaction between the first user and the third user causes both users' scores to exceed the first threshold, the third sharing rule preset by the first user will be automatically applied: the first user will share their private data with the third user according to their customized third sharing scope, while the third user will share data with the first user according to the default rule or their own set rule, i.e., the first sharing scope.

[0084] For example, when user Zhang San rates Li Si higher than 0.7, a bronze badge will appear next to Li Si's avatar as the primary identifier. Zhang San can click on this badge to enter the settings page, where he can adjust the default "Level 1 Friend" sharing range to a custom third sharing range, and additionally add "Recently Listened Music" and "Non-Locationed Images".

[0085] When user Wang Wu's interaction rating with Zhang San also exceeds 0.7, a bronze badge will appear next to Wang Wu's avatar. This will automatically allow Wang Wu to view Zhang San's basic information, text updates, recently listened to music, and non-location-based images, without requiring Zhang San to manually configure it again—thus applying the third sharing scope. The data Wang Wu shares with Zhang San will still be the default first sharing scope content set for the "Level 1 Friend" relationship in Wang Wu's account, such as only including basic information.

[0086] Therefore, users no longer need to go through the tedious privacy settings with each new contact who has reached a certain trust level, greatly improving convenience and efficiency. At the same time, since users can preset different sharing ranges for different trust levels, privacy policies can be more precisely matched to users' own social habits and risk tolerance, enhancing personalization and user control.

[0087] In one possible embodiment, the user interaction information originates from interaction records between a first user and a second user through at least one application, and the interaction records include at least one of the following:

[0088] Chat logs; chat duration and / or frequency; game collaboration records; interaction evaluations; data sharing records.

[0089] The system automatically collects and processes interaction records between the first and second users from the backend of one or more applications shared by both users. These interaction records serve as raw data input for evaluating the quality of their relationship and are the objective basis for calculating the first and second scores.

[0090] Interaction logs encompass various types: chat logs include metadata about the content of text and voice messages exchanged between two parties through instant messaging functions, or the frequency of interactions; chat duration and / or frequency quantify the persistence and regularity of communication, such as the average duration of a single call or the number of interactions per day; game collaboration logs refer to the number of times and success rate of completing matches, tasks, or forming teams together in game applications; interaction evaluations are the attitudes expressed by both parties through interactive behaviors, such as liking, commenting positively, or giving star ratings to each other's posts; and data sharing logs directly reflect the historical behavior of exchanging private data, including the initiation and acceptance of image sharing, video sharing, location sharing, and audio and video chat connections.

[0091] These different types of interaction records are assigned corresponding weights and fed into the scoring algorithm. For example, a successful game collaboration or a long audio / video chat, because it requires a higher level of participation and trust, contributes more to the score improvement than a simple "like". By continuously monitoring these records, the intimacy and activity of user relationships can be dynamically and from multiple perspectives.

[0092] For example, in a super app integrating social networking, gaming, and location services, the interactions between user A and user B are recorded: they chat three times a week for an average of half an hour each, play twenty matches together in a competitive game with a win rate of over 50%, user A frequently likes travel photos posted by user B, and user B has twice shared their real-time location with user A to facilitate offline meetings. All these discrete interaction records are collected, weighted, and aggregated to calculate a high two-way score. This high score then triggers an automatic upgrade of the data sharing scope between the two parties from a basic level to a more lenient level, allowing them to see more detailed online status and gaming achievement history of each other.

[0093] Therefore, by comprehensively utilizing interaction records from multiple dimensions, the true state of user relationships can be assessed more comprehensively and resiliently, significantly improving the accuracy and reliability of scoring. This effectively prevents score manipulation through a single action or misjudgment, ensuring that the final first and second scores more accurately reflect the quality of user interactions, thus providing a solid data foundation for subsequent decisions regarding adjustments to the scope of privacy data sharing.

[0094] In one possible embodiment, step 110 includes:

[0095] Acquire user interaction information of a first user and a second user in at least one social scenario; the social scenario includes at least one of the following: chat scenario, task collaboration scenario, and shared content scenario;

[0096] Based on user interaction information, determine the first user's initial rating for the second user, including:

[0097] The chat score is determined based on the duration of the chat in the chat scenario and the chat feedback value of the first user to the second user;

[0098] The task score is determined based on the number of times the task is completed in the task collaboration scenario and the collaboration feedback value of the first user to the second user;

[0099] The content rating is determined based on the duration of shared viewing in the shared viewing scenario and the content feedback value of the first user to the second user.

[0100] Determine the first score based on chat rating, task rating, and content rating.

[0101] Task collaboration scenarios are social scenarios where users divide tasks, communicate, and cooperate around a specific task goal, such as jointly completing game tasks, project planning, or document editing. Shared content scenarios are social scenarios where users watch videos, live streams, and text / image content together, and interact and communicate in the process.

[0102] Chat feedback score is the first user's evaluation of their chat experience with the second user. It can be comprehensively measured through dimensions such as satisfaction rating after the chat ends and the responsiveness of message replies, reflecting the quality of chat interaction. Collaboration feedback score is the first user's evaluation of the second user's performance during task collaboration, including task completion efficiency, communication and cooperation, and problem-solving abilities. Content feedback score is the first user's evaluation of their interactive experience while sharing content with the second user, including the degree of agreement with the jointly discussed content and the level of interaction activity.

[0103] In chat scenarios, a chat score is calculated based on the chat duration and the first user's feedback to the second user. In task collaboration scenarios, a task score is calculated based on the number of task completions and the first user's feedback to the second user. In shared content scenarios, a content score is calculated based on the shared content viewing time and the first user's feedback to the second user. Finally, a weighted average or more complex machine learning fusion algorithm is used to integrate the scenario scores from these three dimensions, ultimately determining the first score that represents the first user's overall evaluation of the relationship with the second user.

[0104] Chat duration reflects the frequency of communication between users; longer durations generally indicate a closer relationship. Chat feedback reflects the quality of the chat. A weighted calculation is used to combine chat duration and chat feedback. The number of task completions reflects the frequency of cooperation between the two parties in task collaboration, and the collaboration feedback value represents the second user's performance in the collaboration. The duration of shared content viewing reflects the depth of interaction in shared viewing scenarios, and the content feedback value reflects the quality of interaction.

[0105] The chat score, task score, and content score are weighted according to the importance of each scenario in measuring user relationships. For example, the chat scenario has a weight of ω1, the task collaboration scenario has a weight of ω2, and the shared content scenario has a weight of ω3. Where ω1+ω2+ω3=1, the first score is calculated by weighted averaging: first score = ω1×chat score + ω2×task score + ω3×content score. This yields the first user's comprehensive quantitative score for the second user.

[0106] For example, on a work collaboration platform, the interactions between the first and second users were recorded. In chat scenarios, they talked for a total of two hours per week, and the first user frequently provided quick and positive text feedback to the second user's suggestions, resulting in a high chat score. In task collaboration scenarios, they jointly completed five project modules, and the first user gave a five-star rating upon completion each time, generating a high task score. In shared content viewing scenarios, they only watched a training video together once, for half an hour, and had limited interaction, resulting in a relatively low content score. Finally, these three scores were combined according to preset weights to calculate an overall top score.

[0107] By breaking down complex user interactions into different scenarios for independent analysis, we can capture the performance of relationship quality from different perspectives more precisely, avoiding the biases caused by single-dimensional data. For example, two users may have a short chat time but collaborate efficiently on tasks and receive high mutual ratings. This pattern can be accurately captured through scenario-based scoring, and a fair overall evaluation can be obtained after fusion. This multi-scenario fusion scoring mechanism makes the final score more comprehensive and three-dimensional in reflecting the true state of user relationships.

[0108] Therefore, by quantifying interaction metrics in different scenarios, the trust relationship between users can be reflected more accurately. This allows for a comprehensive assessment of user relationships from multiple dimensions, making score-based privacy data access control more closely aligned with actual social relationships, further enhancing the granularity of privacy permission management and effectively protecting user privacy.

[0109] In one possible embodiment, the method further includes:

[0110] Display interactive information, which is used to indicate that the first user and the second user have completed the preset interaction in any social scenario and / or user information is used to indicate the interaction rating progress between the first user and the second user.

[0111] Preset interactions include at least one of the following:

[0112] Chat word count reaches preset word count; chat duration reaches preset value; chat frequency reaches preset frequency; shared content duration reaches preset duration; shared content number reaches preset number of shares; collaboration number reaches preset number of collaborations; collaboration duration reaches preset duration; interaction rating progress is obtained based on any of the following:

[0113] First rating and preset threshold;

[0114] First score, second score, and preset threshold.

[0115] Preset interactions are defined as a series of quantifiable interactions, triggered by conditions including: in chat scenarios, reaching a preset word count, a preset chat duration, or a preset chat frequency; in shared content scenarios, reaching a preset content sharing duration or a preset number of sharing sessions; and in task collaboration scenarios, reaching a preset number of collaboration sessions or a preset collaboration duration. When any condition is met, the user will be notified of this achievement on the interface, for example, by displaying a badge that reads "You have successfully collaborated with the other party 10 times."

[0116] By combining abstract ratings calculated in the background with visual feedback that users can perceive, the aim is to enhance the transparency and engagement of the user experience. Two key types of information are extracted from the collected user interaction data and visualized: the first is historical achievements, indicating the pre-defined interactions completed by the first and second users in a specific social scenario; the second is real-time progress, indicating the degree to which the relationship rating between the two parties is completed relative to a certain goal, also known as the interaction rating progress.

[0117] The interactive rating progress is generated based on how close the score is to the target threshold. One approach is based on one-way evaluation, using a first score and a preset threshold; in this case, the progress value is the ratio of the first score to the preset threshold. The other approach is based on two-way evaluation, using a first score, a second score, and a preset threshold; in this case, the progress value is the ratio of the arithmetic mean of the first and second scores to the preset threshold. This progress value is typically displayed visually as a progress bar, percentage, or level icon.

[0118] For example, in a social application, interaction information would be displayed on User A's profile card for User B. An "Achievements" icon would appear in the achievement area, indicating that their cumulative chat time has exceeded 100 minutes. Simultaneously, a progress bar would show "Trust level about to reach Lv2, 75% complete." This 75% progress is calculated based on User A's rating of User B and the threshold required for Lv2, or based on the ratio of the average mutual ratings to that threshold. Seeing this progress, User A would be more motivated to initiate a video call with User B to push the progress bar to 100%, automatically unlocking the ability to share detailed data.

[0119] By dynamically displaying interactive information related to the progress of the relationship, the guidance and user engagement are significantly enhanced. Showing completed preset interactions provides users with immediate positive feedback, similar to achievements in gamification, motivating them to continue engaging in valuable interactions. Furthermore, visualizing the interaction progress makes the abstract process of increasing trust levels concrete and predictable. Users can clearly see their current relationship status and how far they are from unlocking the next level of functionality. This increases the transparency and controllability of the privacy management process, encouraging users to proactively manage their privacy boundaries through interaction.

[0120] In one possible embodiment, if the first score and / or the second score are greater than or equal to the first threshold, the upgrade animation corresponding to the first threshold is displayed.

[0121] The upgrade animation corresponding to the first threshold features dynamic animation content to intuitively demonstrate to the user that the level of trust between the two parties has reached a new level. This upgrade status can be presented through changes in appearance, the addition of special effects, etc. For example, animations showing two virtual avatars upgrading equipment together or lighting up new badges can create an upgrade atmosphere. Simultaneously, the rating indicator information corresponding to this rating range is displayed in a prominent position on the user's terminal interface, such as displaying the text label "Close Friends" or a specific level badge, allowing the user to clearly understand their current level of trust.

[0122] The system continuously monitors changes in the first and second ratings. When it detects that either or both ratings reach or exceed a first threshold for the first time, a pre-set upgrade animation corresponding to that threshold level is triggered and displayed on the user interface. The upgrade animation corresponding to the first threshold signifies that the relationship between users has officially jumped from a stage of trust to the next higher stage.

[0123] The upgrade animation corresponding to the first threshold is associated with core interactive behaviors that trigger the rating change, such as evaluations and data sharing records. For example, when a long audio or video chat ends, or after a positive like, comment, or evaluation interaction, the rating is recalculated and confirmed to have crossed the first threshold; the animation will then appear at that moment. The animation's content design typically incorporates visual elements symbolizing level advancement, such as icon transformation, a full progress bar, or badge unlocking effects, and directly links to the newly unlocked privacy sharing scope or collaboration features, thus intuitively informing users of the direct results of their interactive behavior.

[0124] For example, in a family photo sharing app, when user A accepts user B's location sharing request for the first time, the system updates both users' ratings based on this significant trust interaction. When user A's initial rating for user B exceeds the first threshold required for the "Close Family" level due to this interaction, a short animation immediately plays on user A's screen: a lock icon symbolizing family relationships slowly unlocks, and the text "Family photo album access unlocked" appears. This animation clearly informs user A that, due to the increased trust level, user B is now authorized to access their private family photo album, making the change in permissions clearly visible.

[0125] This transforms abstract rating changes into vivid and visible visual rewards, greatly enhancing users' emotional engagement and satisfaction, encouraging continuous high-quality interaction, and providing strong immediate feedback and positive incentives.

[0126] The first animation is displayed using a first display parameter, which is used to represent the numerical value of the first rating; the second animation is displayed using a second display parameter, which is used to represent the numerical value of the second rating.

[0127] The first display parameter is a set of parameters used to establish a mapping relationship with the numerical value of the first rating. It includes attributes such as the color intensity, size, playback speed, and transparency of the animation. Changes in the first display parameter intuitively present the level of the first rating. The second display parameter is a set of parameters associated with the numerical value of the second rating. It also consists of attributes such as the color, size, speed, and transparency of the animation, and is used to visually display the specific numerical value of the second rating.

[0128] The first animation is rendered and displayed based on the first display parameters, using dynamic visual effects to reflect the first user's rating of the second user. The second animation is generated and presented based on the second display parameters, used to visually display the second user's rating of the first user.

[0129] Establish a mapping relationship between the first rating and the first display parameters, and between the second rating and the second display parameters. For example, when the first rating is between 0 and 30, the first animation is blue, small in size, plays slowly, and has high transparency; as the first rating increases, the animation color gradually changes to red, the size increases, the playback speed increases, and the transparency decreases. Similarly, establish a similar mapping rule for the second display parameters for the second rating. After calculating the first and second ratings, render the first animation with the first display parameters and the second animation with the second display parameters according to the corresponding mapping rules, and display them on the user's terminal interface, allowing the user to intuitively perceive the rating status through the visual changes in the animation.

[0130] like Figure 2c As shown, the first animation 213 is displayed with a first display parameter, which is used to represent the numerical value of the first score and is yellow; the second animation 214 is displayed with a second display parameter, which is used to represent the numerical value of the second score and is green.

[0131] Therefore, by displaying animations with different parameters, the ways users obtain rating information are further enriched. By associating ratings with display parameters such as the animation's color, size, speed, and transparency, the rating situation is presented in a dynamic and visually appealing way. Compared to simple progress bars or charts, this is more visually impactful and engaging, attracting user attention and helping them understand the differences in trust levels between individuals more quickly and intuitively.

[0132] In one possible embodiment, the interaction record includes a first interaction record and a second interaction record, and the first rating and / or the second rating is obtained by a weighted sum of the values ​​of the first interaction record and the second interaction record;

[0133] The first interaction record and / or the second interaction record includes any of the following:

[0134] Chat logs; chat duration and / or frequency; game collaboration records; interaction evaluations; data sharing records.

[0135] The collected raw interaction records are categorized into different classes based on their attributes or importance, such as first interaction record and second interaction record. Different weights are assigned to records in different classes, and the first score and / or second score are obtained by calculating the weighted sum of these records.

[0136] Both the first and second interaction records can be selected from common interaction types, such as chat logs, chat duration and / or frequency, game collaboration records, interaction evaluations, and data sharing records. The difference between the first and second interaction records lies in the weighting coefficients assigned to them in the scoring model. This weighting can be based on various strategies: for example, it can be differentiated according to the importance of the interaction type, assigning behaviors that demonstrate deep trust to the first interaction record with higher weight, and assigning routine interactions to the second interaction record with lower weight; or it can be differentiated according to time, assigning recent interactions to the first interaction record with higher weight to reflect the latest state of the relationship, and assigning older interactions to the second interaction record with diminished weight.

[0137] Specifically, the score is calculated as follows: (number of first interaction records * weight W1) + (value of second interaction record * weight W2), where W1 and W2 are preset weight coefficients.

[0138] By employing a weighted sum model, the actual contribution of different interactive behaviors to trust relationships can be more accurately reflected. For example, the impact of a single key data sharing record on trust building should be far greater than ten simple "likes." The weighted model perfectly captures this difference by assigning higher weights to the former, enabling the final score to more realistically and effectively characterize the quality of user relationships. This provides a more reliable and differentiated decision-making basis for the dynamic adjustment of the scope of privacy data sharing, enhancing the adaptability and accuracy of the score.

[0139] In one possible embodiment, step 120 may specifically include the following steps:

[0140] If both the first score and the second score fall within the first score range, display the privacy data corresponding to the first score range.

[0141] The privacy data includes at least one of the following: task collaboration data, social dynamic information, and chat logs.

[0142] The first rating range is a pre-defined numerical range used to classify the level of trust between users. Different rating ranges correspond to different privacy data access permissions and are an important basis for controlling the display of privacy data. Task collaboration data refers to data generated in task collaboration scenarios, such as task plans, execution progress, and task outcome documents, containing key information from the user collaboration process. Social dynamic information includes users' personal life updates, opinion sharing, and interest displays, reflecting their personal status and life trajectory. Chat history consists of text, voice, and image communication information generated between users in chat scenarios, directly reflecting social interaction.

[0143] Multiple rating ranges are pre-defined, such as [0-30), [30-60), [60-85], and [85-100]. For each rating range, the types of privacy data that can be displayed are defined. For example, when both the first and second ratings fall within the first rating range of [60-85], the corresponding displayable privacy data includes task collaboration data and social media activity information; if both the first and second ratings fall within [85-100], task collaboration data, social media activity information, and chat logs can be displayed. This setting is based on the user trust level represented by different rating ranges; the higher the trust level, the more comprehensive the privacy data that can be accessed.

[0144] The calculated first and second scores are compared with preset score intervals to determine their respective intervals. If both the first and second scores fall within the same first score interval, the privacy data corresponding to that score interval is displayed on the first user's terminal, thus dynamically controlling the display of privacy data based on the level of trust between users.

[0145] like Figure 2a As shown, when both the first score and the second score fall within the first score range, the privacy data 210 corresponding to the first score range is displayed.

[0146] Therefore, by setting scoring ranges and corresponding privacy data, privacy access management becomes more hierarchical and refined. Releasing appropriate privacy data based on different levels of trust between users effectively protects user privacy and prevents excessive leakage of sensitive information. Furthermore, when user trust reaches a certain level, it promotes deeper social interaction, enhances the user experience within the social system, and achieves a balance between privacy protection and social interaction.

[0147] In one possible embodiment, upon detecting user interaction information in each of the social scenarios, interactive animation information is displayed to indicate that the first user and the second user have completed the interaction in any of the social scenarios.

[0148] Based on the user interaction information, rating progress information is displayed, which is used to represent the numerical values ​​of the first rating and the second rating.

[0149] Interactive animated information is a visually dynamic display that is triggered after a user completes an interaction in a social scenario. It uses animation to intuitively indicate that the first and second users have completed their interaction in a specific social context, enhancing the user's perception of interaction. Rating progress information visually presents the magnitude of the first and second ratings, which can be displayed through progress bars, charts, etc., helping users intuitively understand the quantified rating of their mutual trust levels.

[0150] When user interaction is detected in any social scenario, the system triggers the display of interactive animation information. For example, in a chat scenario, when two parties complete a chat conversation, the system displays specific interactive animations on the terminal interfaces of the first and second users according to preset animation templates. These animations may include two virtual avatars clinking glasses or shaking hands, visually demonstrating to the users that the interaction has been completed.

[0151] Based on the calculated first and second scores, the score values ​​are converted into visual scoring progress information. A progress bar can be used, mapping the scoring range to the length of the bar. For example, if the scoring range is 0-100, a full bar represents 100 points. When the first score is 70, the progress bar fills to the 70% mark and displays the corresponding score, allowing users to intuitively understand the scoring situation of both parties.

[0152] like Figure 2b As shown, when user interaction information is detected in each of the aforementioned social scenarios, interactive animation information 211 is displayed; and rating progress information 212 is displayed based on the user interaction information.

[0153] Therefore, by adding interactive animation information and rating progress information, the user's interactive experience in the social system is further enhanced. Interactive animation information can provide timely and intuitive feedback on user interaction behavior, enhancing the fun and ritual of interaction and stimulating users' enthusiasm for participating in social interactions; rating progress information allows users to clearly understand the quantitative rating of the level of trust between each other, making the presentation of social relationships more transparent, helping users to more accurately grasp the social distance with others, and also providing a more intuitive reference for rating-based privacy data access control.

[0154] In one possible embodiment, upon entering an extended reality (XR) social space, multidimensional social data is collected, which includes at least one of the following: user personality test data, behavioral trajectory data, preference data, and real-time interaction data.

[0155] Based on the multidimensional social data, a user profile tag matrix is ​​generated;

[0156] The similarity of tags between users in the social space is calculated based on the user profile tag matrix, and the user information of the third user is marked and displayed. The similarity of the tags of the third user and the first user is higher than a first preset threshold.

[0157] Extended Reality (XR) social spaces include immersive social interaction virtual spaces constructed by integrating Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) technologies. A user profile tag matrix is ​​a matrix structure composed of multi-dimensional tags used to comprehensively characterize user features; each tag represents a specific attribute or behavioral characteristic of the user. Tag similarity is a numerical metric calculated using a specific algorithm to measure the degree of similarity between two user profile tag matrices.

[0158] When users enter the XR social space, real-time data collection includes personality test data, behavioral trajectory data, preference data, and real-time interaction data. For example, gesture capture devices collect body movements to form behavioral trajectory data, and personality test data is obtained from user-completed questionnaires. The collected multi-dimensional social data is analyzed and processed, transforming data features into corresponding tags. For instance, a "music lover" tag is generated based on a user's preference for music-related content, and an "extroverted" tag is generated based on personality test results. These tags are then integrated to construct a user profile tag matrix, describing user characteristics from multiple dimensions.

[0159] Algorithms such as cosine similarity are used to calculate the label similarity between the user profile label matrices of the first user and the third user within the social space. If the label similarity between the third user and the first user is higher than a first preset threshold, the system will highlight and display the third user's user information, such as avatar, nickname, and key tags, in the XR social space to facilitate the first user's quick identification of potential like-minded social contacts.

[0160] Therefore, in XR social spaces, by collecting multi-dimensional social data to generate precise user profile tag matrices and displaying potential social partners based on tag similarity, it is possible to break through the limitations of traditional social recommendations. Leveraging the immersive characteristics of XR technology, it can uncover similarities between users from multiple dimensions. This helps users efficiently discover like-minded partners in virtual social spaces, improving the accuracy and efficiency of social matching, and enhancing users' social experience and willingness to interact in XR social spaces.

[0161] In one possible embodiment, recruitment information from at least one company is displayed. The recruitment information includes: company identification information and dynamic matching information. The display parameters of the dynamic matching information are used to characterize the matching degree between the company's recruitment information and the first user.

[0162] Based on the user interaction information, determining the first user's first rating of the second user and the second user's second rating of the first user includes:

[0163] Based on the user interaction information, a first rating of the first user to the enterprise and a second rating of the enterprise to the first user are determined; the user interaction information includes at least one of the following: interview information, interview score, online written test information, written test score, and browsing information.

[0164] If both the first score and the second score are within the first score range, determine the first score level corresponding to the first score range;

[0165] Displays the rating identifier information corresponding to the first rating level and at least part of the recruitment information.

[0166] The "enterprise" side refers to various business organizations that post recruitment needs. Recruitment information is used by enterprises to recruit talent, including enterprise identification information and dynamic matching information. The display parameters of the dynamic matching information are visual parameters used to present the match between the enterprise's recruitment information and the first user, such as color intensity, font size, and progress bar fill level. Changes in these display parameters visually demonstrate the degree of match.

[0167] like Figure 3 As shown, recruitment information from at least one company is displayed. The recruitment information includes: company identification information 215 and dynamic matching information 216. The display parameters of the dynamic matching information 216 are used to characterize the matching degree between the company's recruitment information and the first user.

[0168] Interview information records relevant data about the first user's participation in company interviews, including interview time, interviewer evaluation, interview questions and answers, etc. Interview score is a quantitative score given by the company to the first user's interview performance. Online test information records the process data of the first user's participation in the company's online written test, such as answer records and answer time. Written test score is the score given by the company to the first user's online written test score.

[0169] Browsing information refers to the user's viewing behavior data when viewing company recruitment information, including browsing duration and number of views. The first rating level is a tier set for different first rating intervals, used to identify the level of matching and evaluation between the first user and the company.

[0170] The system acquires recruitment information from at least one company and integrates and displays the company's identification information with dynamic matching information. When displaying dynamic matching information, a pre-set algorithm analyzes the company's job requirements and the first user's personal information and behavioral data to calculate the matching degree, which is then converted into corresponding display parameters. For example, when the matching degree is high, the dynamic matching information is displayed in a bright color and a larger font; when the matching degree is low, it is presented in a lighter color and a smaller font.

[0171] Collect user interaction information between the first user and the company, including interview information, interview scores, online written test information, written test scores, and browsing information. Based on this interaction information, determine the first user's first rating of the company and the company's second rating of the first user. For example, if the first user actively participates in the interview and performs well, and spends a lot of time browsing job postings frequently, these behaviors will improve the first user's rating of the company; while the company will evaluate the first user based on interview scores, written test scores, etc., and give a second rating.

[0172] The calculated first and second scores are compared with a preset first score interval. If both fall within a certain first score interval, the first score level corresponding to that interval is determined. Each score interval corresponds to a different score level, such as [0-30] corresponding to "low matching level" and [85-100] corresponding to "high matching level".

[0173] The system displays rating information corresponding to the first rating level, such as a text label or exclusive badge for "High Match Level," along with at least a portion of the job postings corresponding to that rating level. For high match levels, it displays complete job details and company information; for lower levels, it only displays the company name and a brief job description, allowing users to quickly understand their match with the company and the relevant job postings.

[0174] Therefore, by dynamically matching information and displaying the matching degree intuitively, a score and rating level are determined based on rich user interaction information, and relevant content is displayed accordingly. On the one hand, this helps users more clearly understand their matching degree with the job openings and accurately obtain suitable recruitment information.

[0175] In one possible embodiment, job application information of at least one candidate is displayed, the at least one candidate including the second user; based on the user interaction information, a first rating from the first user to the second user and a second rating from the second user to the first user are determined, including:

[0176] If both the first rating and the second rating fall within the first rating range, determine the first rating level corresponding to the first rating range; display the rating identifier information corresponding to the first rating level and at least part of the resume information of the second user.

[0177] Job application information comprises the personal data submitted by candidates during the job search process and related information generated during this process. It includes resume information such as basic personal details, educational background, work experience, skills and certifications, interview performance records, and written test scores. Resume information is the core material candidates use to showcase their background, abilities, and experience; it is a crucial component of job application information and includes various formats such as text descriptions and certificate images.

[0178] Retrieve the application information of at least one candidate and display it on the interface. During the display, extract and integrate key candidate information, such as name, applied position, and main work experience, and present it in a concise and clear manner, enabling first-time users, such as corporate recruiters, to quickly browse and perform initial screening.

[0179] The system collects user interaction information between the first and second users. This information includes, but is not limited to, conversations during interviews, interview scores, online written test information, written test scores, and the first user's browsing information of the second user's application materials. Based on this interaction information, a specific scoring algorithm is used to determine the first user's first rating of the second user and the second user's second rating of the first user. For example, if the second user demonstrates professional knowledge and good communication skills during the interview, it will improve the first user's rating of them; if the second user actively expresses interest in the company and their willingness to join, it will also correspondingly increase the rating of the first user.

[0180] The calculated first and second scores are compared with a preset first score range. If both scores fall within the same first score range (e.g., [60-85)), the corresponding first score level is determined, such as "medium match level". Each score range has a pre-defined level to clearly identify the degree of match and evaluation between the two parties.

[0181] The system displays rating information corresponding to the first rating level, such as a text label or specific icon for "Medium Match Level," and also shows at least part of the resume information of the second user corresponding to that rating level. For higher rating levels, it displays complete work experience, detailed project results, etc.; for lower rating levels, it displays basic personal information and a simple summary of education and work experience, enabling the first user to quickly understand the candidate's match with the position and the candidate's core competencies.

[0182] Therefore, by displaying candidate application information and combining it with user interaction data to determine scores and rating levels, this system provides recruiters with a more efficient and intuitive way to screen talent. The scoring mechanism based on interactive information comprehensively reflects the fit between candidates and company needs, as well as the mutual evaluations during the interaction process. Displaying rating levels and corresponding resume information helps recruiters quickly identify high-quality candidates, reducing screening time and improving recruitment efficiency.

[0183] In the embodiments of this application, by acquiring user interaction information of the first user and the second user in various social scenarios, and by comprehensively collecting user interaction behavior data in different scenarios, the relationship between users can be reflected more realistically and comprehensively, laying a solid foundation for accurate analysis of user relationships. Based on the user interaction information, a first rating from the first user to the second user and a second rating from the second user to the first user are determined. The complex interaction behavior between the first user and the second user is transformed into quantitative indicators for evaluating both parties. The first and second ratings are updated continuously as user interaction behavior changes, enabling timely capture of changes in user relationships. Based on the first and second ratings, the evaluation of each other by the first user and the second user can be comprehensively considered, adjusting the scope of privacy data sharing between the first user and the second user, improving the flexibility and real-time nature of privacy sharing, achieving refined management of privacy data, and effectively improving the security and effectiveness of social interaction.

[0184] The privacy data sharing method provided in this application can be executed by a privacy data sharing device. This application uses an example of a privacy data sharing device executing the privacy data sharing method to illustrate the privacy data sharing device provided in this application.

[0185] Figure 4 This is a block diagram of a privacy data sharing device provided in an embodiment of this application. The device 400 includes:

[0186] The acquisition module 410 is used to acquire user interaction information between the first user and the second user.

[0187] The determining module 420 is used to determine, based on the user interaction information, the first user's first rating of the second user and the second user's second rating of the first user;

[0188] The adjustment module 430 is used to adjust the scope of privacy data sharing between the first user and the second user based on the first score and the second score.

[0189] In one possible embodiment, the adjustment module 430 is specifically used for:

[0190] When both the first score and the second score are greater than or equal to the first threshold, the scope of sharing privacy data between the first user and the second user is the first sharing scope.

[0191] When both the first score and the second score are greater than or equal to the second threshold, the scope of sharing of privacy data between the first user and the second user is the second sharing scope.

[0192] The second threshold is greater than the first threshold, and the first shared range at least partially overlaps with the second shared range.

[0193] In one possible embodiment, the adjustment module 430 is specifically used for:

[0194] If both the first score and the second score are greater than or equal to the first threshold, the first collaboration function between the first user and the second user is enabled, and the privacy data obtained by the first collaboration function is within the first sharing range.

[0195] If both the first score and the second score are greater than or equal to the second threshold, the second collaboration function between the first user and the second user is enabled, and the privacy data obtained by the second collaboration function is within the second sharing scope.

[0196] The second threshold is greater than the first threshold, and the first shared range at least partially overlaps with the second shared range.

[0197] In one possible embodiment, the first shared range is located within the second shared range.

[0198] In one possible embodiment, the privacy data included in the first sharing scope includes at least one of the following: personal information; location information; social activity; and application usage data.

[0199] In one possible embodiment, the privacy data included in the second sharing scope includes at least one of the following: personal information; location information; social activity; application usage data; images; videos; and files.

[0200] In one possible embodiment, the device 400 may further include:

[0201] The display module is used to display the first identifier of the second user on the first user's first terminal, the first identifier being used to indicate that the first score is greater than a first threshold; the first user presets or adjusts the sharing range of the privacy data corresponding to the first identifier to a third sharing range based on the first identifier;

[0202] The sharing module is configured to, when both the third rating of the first user to the third user and the fourth rating of the third user to the first user are greater than the first threshold, allow the first user to share privacy data with the third user based on the third sharing range, and allow the third user to share privacy data with the first user based on the first sharing range.

[0203] In one possible embodiment, the user interaction information originates from the interaction records of the first user and the second user through at least one application, and the interaction records include at least one of the following: chat logs; chat duration and / or frequency; game collaboration records; interaction evaluations; and data sharing records.

[0204] In one possible embodiment, the acquisition module 410 is specifically used for:

[0205] Acquire user interaction information of a first user and a second user in at least one social scenario; the social scenario includes at least one of the following: chat scenario, task collaboration scenario, and shared content scenario;

[0206] The determining module 420 is specifically used for:

[0207] A chat score is determined based on the chat duration in the chat scenario and the chat feedback value from the first user to the second user.

[0208] The task score is determined based on the number of times the task is completed in the task collaboration scenario and the collaboration feedback value of the first user to the second user;

[0209] The content rating is determined based on the shared viewing time in the shared viewing scenario and the content feedback value from the first user to the second user.

[0210] The first score is determined by considering the chat score, the task score, and the content score.

[0211] In one possible embodiment, the device 400 may further include:

[0212] The display module is used to display interactive information, which is used to indicate that the first user and the second user have completed a preset interaction in any social scenario and / or the user information is used to indicate the interaction rating progress between the first user and the second user;

[0213] The preset interaction includes at least one of the following: the number of words in the chat reaches a preset number; the chat duration reaches a preset value; the chat frequency reaches a preset frequency; the duration of shared content reaches a preset duration; the number of times shared content reaches a preset number of shares; the number of collaborations reaches a preset number of times; the collaboration duration reaches a preset duration; the interaction rating progress is obtained based on any one of the following: the first rating and a preset threshold; the first rating, the second rating, and the preset threshold.

[0214] In one possible embodiment, the device 400 may further include:

[0215] The display module is used to display the upgrade animation corresponding to the first threshold when the first score and / or the second score is greater than or equal to the first threshold.

[0216] In one possible embodiment, the interaction record includes a first interaction record and a second interaction record, wherein the first rating and / or the second rating is obtained by a weighted sum of the first interaction record and the second interaction record;

[0217] The first interaction record and / or the second interaction record include any one of the following: chat history; chat duration and / or frequency; game collaboration record; interaction evaluation; data sharing record.

[0218] In the embodiments of this application, by acquiring user interaction information of the first user and the second user in various social scenarios, and by comprehensively collecting user interaction behavior data in different scenarios, the relationship between users can be reflected more realistically and comprehensively, laying a solid foundation for accurate analysis of user relationships. Based on the user interaction information, a first rating from the first user to the second user and a second rating from the second user to the first user are determined. The complex interaction behavior between the first user and the second user is transformed into quantitative indicators for evaluating both parties. The first and second ratings are updated continuously as user interaction behavior changes, enabling timely capture of changes in user relationships. Based on the first and second ratings, the evaluation of each other by the first user and the second user can be comprehensively considered, adjusting the scope of privacy data sharing between the first user and the second user, improving the flexibility and real-time nature of privacy sharing, achieving refined management of privacy data, and effectively improving the security and effectiveness of social interaction.

[0219] The privacy data sharing device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. It can also be a server, network attached storage (NAS), personal computer (PC), television set (TV), ATM, or self-service machine, etc. This application embodiment does not specifically limit the device.

[0220] The privacy data sharing device in this application embodiment can be a device with an action system. The action system can be an Android action system, an iOS action system, or other possible action systems; this application embodiment does not specifically limit it.

[0221] The privacy data sharing device provided in this application embodiment can implement the various processes implemented in the above method embodiments, and will not be described again here to avoid repetition.

[0222] Optionally, such as Figure 5 As shown, this application embodiment also provides an electronic device 510, including a processor 511, a memory 512, and a program or instructions stored in the memory 512 and executable on the processor 511. When the program or instructions are executed by the processor 511, they implement the various steps of any of the above-described privacy data sharing method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0223] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0224] Figure 6 A schematic diagram of the hardware structure of an electronic device to implement an embodiment of this application.

[0225] The electronic device 600 includes, but is not limited to, components such as: radio frequency unit 601, network module 602, audio output unit 603, input unit 604, sensor 605, display unit 606, user input unit 607, interface unit 608, memory 609, and processor 610.

[0226] Those skilled in the art will understand that the electronic device 600 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 610 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 6 The electronic device structure shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0227] The processor 610 is used to acquire user interaction information between the first user and the second user.

[0228] The processor 610 is further configured to determine, based on the user interaction information, a first rating of the first user to the second user and a second rating of the second user to the first user;

[0229] The processor 610 is also configured to adjust the scope of privacy data sharing between the first user and the second user based on the first score and the second score.

[0230] Optionally, the processor 610 is further configured to, when both the first score and the second score are greater than or equal to a first threshold, define the sharing range of privacy data between the first user and the second user as a first sharing range;

[0231] The processor 610 is further configured to, when both the first score and the second score are greater than or equal to a second threshold, define the sharing range of privacy data between the first user and the second user as a second sharing range; wherein the second threshold is greater than the first threshold, and the first sharing range at least partially overlaps with the second sharing range.

[0232] Optionally, the processor 610 is further configured to enable a first collaboration function between the first user and the second user when both the first score and the second score are greater than or equal to a first threshold, wherein the privacy data obtained by the first collaboration function is within a first sharing range.

[0233] The processor 610 is further configured to enable a second collaboration function between the first user and the second user when both the first score and the second score are greater than or equal to a second threshold, wherein the privacy data acquired by the second collaboration function is located within a second sharing range; the second threshold is greater than the first threshold, and the first sharing range at least partially overlaps with the second sharing range.

[0234] Optionally, the first sharing range is located within the second sharing range.

[0235] Optionally, the privacy data included in the first sharing scope includes at least one of the following: personal information; location information; social dynamics; application usage data.

[0236] Optionally, the privacy data included in the second sharing scope includes at least one of the following: personal information; location information; social activity; application usage data; images; videos; and files.

[0237] The display unit 606 is further configured to display the first identifier of the second user on the first user's first terminal, the first identifier being used to indicate that the first score is greater than a first threshold; the first user presets or adjusts the sharing range of the privacy data corresponding to the first identifier to a third sharing range based on the first identifier;

[0238] The processor 610 is further configured to, when both the third rating of the first user to the third user and the fourth rating of the third user to the first user are greater than the first threshold, share privacy data with the third user based on the third sharing range, and the third user shares privacy data with the first user based on the first sharing range.

[0239] Optionally, the user interaction information originates from the interaction records between the first user and the second user through at least one application, and the interaction records include at least one of the following: chat logs; chat duration and / or frequency; game collaboration records; interaction evaluations; and data sharing records.

[0240] Optionally, the processor 610 is further configured to acquire user interaction information of the first user and the second user in at least one social scenario; the social scenario includes at least one of the following: chat scenario, task collaboration scenario, and shared content scenario;

[0241] The processor 610 is also configured to determine a chat score based on the chat duration in the chat scenario and the chat feedback value from the first user to the second user;

[0242] The processor 610 is also configured to determine a task score based on the number of times the task is completed in the task collaboration scenario and the collaboration feedback value of the first user to the second user;

[0243] The processor 610 is also configured to determine a content rating based on the shared viewing time in the shared viewing scenario and the content feedback value from the first user to the second user.

[0244] The processor 610 is also configured to determine the first score by evaluating the chat score, the task score, and the content score.

[0245] Optionally, the display unit 606 is also used to display interactive information, which is used to indicate that the first user and the second user have completed a preset interaction in any social scenario and / or the user information is used to indicate the interaction rating progress between the first user and the second user.

[0246] The preset interaction includes at least one of the following: the number of words in the chat reaches a preset number; the chat duration reaches a preset value; the chat frequency reaches a preset frequency; the duration of shared content reaches a preset duration; the number of times shared content reaches a preset number of shares; the number of collaborations reaches a preset number of times; the collaboration duration reaches a preset duration; the interaction rating progress is obtained based on any one of the following: the first rating and a preset threshold; the first rating, the second rating, and the preset threshold.

[0247] Optionally, the display unit 606 is further configured to display an upgrade animation corresponding to the first threshold when the first score and / or the second score is greater than or equal to the first threshold.

[0248] Optionally, the interaction record includes a first interaction record and a second interaction record, and the first rating and / or the second rating is obtained by a weighted sum of the first interaction record and the second interaction record;

[0249] The first interaction record and / or the second interaction record include any one of the following: chat history; chat duration and / or frequency; game collaboration record; interaction evaluation; data sharing record.

[0250] In the embodiments of this application, by acquiring user interaction information of the first user and the second user in various social scenarios, and by comprehensively collecting user interaction behavior data in different scenarios, the relationship between users can be reflected more realistically and comprehensively, laying a solid foundation for accurate analysis of user relationships. Based on the user interaction information, a first rating from the first user to the second user and a second rating from the second user to the first user are determined. The complex interaction behavior between the first user and the second user is transformed into quantitative indicators for evaluating both parties. The first and second ratings are updated continuously as user interaction behavior changes, enabling timely capture of changes in user relationships. Based on the first and second ratings, the evaluation of each other by the first user and the second user can be comprehensively considered, adjusting the scope of privacy data sharing between the first user and the second user, improving the flexibility and real-time nature of privacy sharing, achieving refined management of privacy data, and effectively improving the security and effectiveness of social interaction.

[0251] It should be understood that, in this embodiment, the input unit 604 may include a graphics processing unit (GPU) 6041 and a microphone 6042. The GPU 6041 processes image data of still images or video images obtained by an image capture device (such as a camera) in video image capture mode or image capture mode. The display unit 606 may include a display panel 6061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 607 includes at least one of a touch panel 6071 and other input devices 6072. The touch panel 6071 is also called a touch screen. The touch panel 6071 may include a touch detection device and a touch controller. Other input devices 6072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, and joysticks, which will not be described in detail here. The memory 609 can be used to store software programs and various data, including but not limited to applications and motion systems. Processor 610 can integrate an application processor and a modem processor. The application processor mainly handles the action system, user page, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into processor 610.

[0252] The memory 609 can be used to store software programs and various data. The memory 609 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store the operating system, application programs or instructions required for at least one function (such as sound playback, image playback, etc.). Furthermore, the memory 609 may include volatile memory or non-volatile memory, or it may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus RAM (DRRAM). The memory 609 in this embodiment includes, but is not limited to, these and any other suitable types of memory.

[0253] Processor 610 may include one or more processing units; optionally, processor 610 integrates an application processor and a modem processor, wherein the application processor mainly handles operations involving the operating system, user interface, and applications, and the modem processor mainly handles wireless communication signals, such as a baseband processor. It is understood that the aforementioned modem processor may also not be integrated into processor 610.

[0254] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described privacy data sharing method embodiments and achieve the same technical effects. To avoid repetition, they will not be described again here.

[0255] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0256] This application embodiment also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-described privacy data sharing method embodiments and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0257] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0258] This application provides a computer program product that is stored in a storage medium and executed by at least one processor to implement the various processes of the above-described privacy data sharing method embodiments, and can achieve the same technical effects. To avoid repetition, it will not be described again here.

[0259] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0260] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0261] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of this application.

Claims

1. A method of sharing of privacy data, characterized by, The method comprises: obtaining user interaction information of a first user and a second user; determining a first score of the first user to the second user and a second score of the second user to the first user according to the user interaction information; adjusting a sharing range of privacy data between the first user and the second user according to the first score and the second score.

2. The method of claim 1, wherein, The adjusting of the sharing range of the privacy data between the first user and the second user according to the first score and the second score comprises: in a case that the first score and the second score are both greater than or equal to a first threshold, the sharing range of the privacy data between the first user and the second user is a first sharing range; in a case that the first score and the second score are both greater than or equal to a second threshold, the sharing range of the privacy data between the first user and the second user is a second sharing range; the second threshold is greater than the first threshold, and the first sharing range at least partially overlaps with the second sharing range.

3. The method of claim 1, wherein, The adjusting of the sharing range of the privacy data between the first user and the second user according to the first score and the second score comprises: in a case that the first score and the second score are both greater than or equal to a first threshold, a first collaboration function between the first user and the second user is enabled, and the first collaboration function obtains privacy data within a first sharing range; in a case that the first score and the second score are both greater than or equal to a second threshold, a second collaboration function between the first user and the second user is enabled, and the second collaboration function obtains privacy data within a second sharing range; the second threshold is greater than the first threshold, and the first sharing range at least partially overlaps with the second sharing range.

4. The method according to claim 2 or 3, characterized in that, The privacy data included in the first sharing range comprises at least one of: personal information; location information; social dynamics; application usage data.

5. The method according to claim 2 or 3, characterized in that, The privacy data included in the second sharing range comprises at least one of: personal information; location information; social dynamics; application usage data; images; videos; files.

6. The method of claim 1, wherein, The method further comprises: displaying a first identifier of the second user on a first terminal of the first user, the first identifier being used to indicate that the first score is greater than a first threshold, and the first user presets or adjusts a sharing range of privacy data corresponding to the first identifier as a third sharing range based on the first identifier; in a case that a third score of the first user to a third user and a fourth score of the third user to the first user are both greater than the first threshold, the first user shares privacy data with the third user based on the third sharing range, and the third user shares privacy data with the first user based on a first sharing range.

7. The method of claim 1, wherein, The user interaction information is derived from interaction records of the first user and the second user through at least one application program, the interaction records comprise at least one of: chat records; chat duration and / or frequency; game collaboration records; interaction evaluation; data sharing records.

8. The method of claim 1, wherein, The obtaining the user interaction information of the first user and the second user comprises: obtaining user interaction information of the first user and the second user in at least one social scene; the social scene comprises at least one of the following: a chat scene, a task cooperation scene and a content co-watching scene; The determining the first score of the first user to the second user according to the user interaction information comprises: determining a chat score according to a chat duration in the chat scene and a chat feedback value of the first user to the second user; determining a task score according to a task completion number in the task cooperation scene and a cooperation feedback value of the first user to the second user; determining a content score according to a content co-watching duration in the content co-watching scene and a content feedback value of the first user to the second user; determining the first score according to the chat score, the task score and the content score.

9. The method of claim 1, wherein, The method further comprises: displaying interaction information, the interaction information being used to indicate that the first user and the second user have completed a preset interaction in any social scene and / or the user information being used to indicate an interaction score progress between the first user and the second user; The preset interaction comprises at least one of the following: chat word number reaching a preset word number; chat duration reaching a preset value; chat frequency reaching a preset frequency; content sharing duration reaching a preset duration; content sharing number reaching a preset sharing number; cooperation number reaching a preset number; cooperation duration reaching a preset duration; The interaction score progress is obtained based on any one of the following: the first score and a preset threshold value; the first score, the second score and a preset threshold value.

10. An apparatus for sharing of privacy data, characterized by comprises: an obtaining module, configured to obtain user interaction information of a first user and a second user; a determining module, configured to determine a first score of the first user to the second user and a second score of the second user to the first user according to the user interaction information; an adjusting module, configured to adjust a sharing range of privacy data between the first user and the second user according to the first score and the second score.

11. An electronic device, comprising: comprises a processor and a memory, the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to implement the steps of the privacy data sharing method according to any one of claims 1-9.

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