Method and device for constructing social network relationship graph, equipment and storage medium

Abstract

The invention discloses a method and device for constructing a social network relationship graph, equipment and a storage medium, and relates to the technical field of data processing. In the method, in response to a click operation of a first user, target social software is determined; if the target social software is authorized, obtaining target account information; judging whether the target account information is consistent with the personal information or not; when the target account information is consistent with the personal information, determining to acquire first target data from the target social software; processing the first target data to obtain multiple pieces of network relationship information; and constructing the multiple pieces of network relation information to obtain a target social network relation graph, and displaying the target social network graph to the first user, so that the first user can check the target social network graph corresponding to the target social software. By implementing the technical scheme provided by the invention, the efficiency of constructing the social network relationship graph is remarkably improved, and the problem of low efficiency during manual construction is solved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to a method, device, equipment and storage medium for constructing a social network relationship graph. Background Art

[0002] With the popularity of social media and the development of Internet technology, social data has shown an exponential growth. Constructing social network relationship graphs has become an effective means to better understand and utilize these massive data, so as to mine information with practical value. As a data structure, social network relationship graphs can clearly display the associations and interaction data between users, which is of great significance for in-depth understanding of user behavior, social relationships, and information dissemination paths.

[0003] For users, social network relationship maps help them understand their social circles more comprehensively and identify potential friends, partners or business opportunities. At the same time, by analyzing social network relationship maps, users can better understand the dissemination path and influence of information in social networks, thereby improving the efficiency and accuracy of information acquisition. However, when users currently build social network relationship maps, they usually need to manually obtain the corresponding friend information from each social software, and then aggregate the friend information to form a complete social network relationship map. However, this method takes a long time, resulting in low efficiency in building social network relationship maps.

[0004] Therefore, there is an urgent need for a method, device, equipment and storage medium for constructing a social network relationship graph that can solve the above technical problems. Summary of the invention

[0005] The present application provides a method, apparatus, device and storage medium for constructing a social network relationship graph. The method automatically obtains first target data corresponding to a target social software, processes the first target data, and then constructs a social network relationship graph, which significantly improves the efficiency of constructing the social network relationship graph and solves the problem of low efficiency during manual construction.

[0006] In a first aspect, the present application provides a method for constructing a social network relationship graph, which is applied to a server, and the method includes: determining a target social software in response to a click operation of a first user; determining whether the target social software is authorized; if the target social software is authorized, obtaining target account information, the target account information being the account information registered and logged in on the target social software; determining whether the target account information is consistent with personal information, the personal information being the identity information corresponding to the first user; when the target account information is consistent with the personal information, confirming that the first target data is obtained from the target social software; processing the first target data to obtain multiple network relationship information; constructing multiple network relationship information to obtain a target social network relationship graph, and displaying the target social network graph to the first user, so that the first user can view the target social network graph corresponding to the target social software.

[0007] By adopting the above technical solution, in response to the click operation of the first user, the social software that needs to construct the social network relationship map is determined, and by verifying whether the target account information is consistent with the personal information, when the target account information is consistent with the personal information, it is confirmed that the first user has the authority to obtain the corresponding first target data in the target social software, and the first target data is processed to obtain multiple network relationship information, so that the target social network relationship map can be constructed through the multiple network relationship information in the future, and the data on the target social software can be automatically obtained, avoiding the tedious process of manual search and sorting of data; and then the constructed target social network relationship map is displayed to the first user, so that the first user can quickly view and analyze the target social network relationship map without waiting for the completion of the manual construction process, which significantly improves the efficiency of constructing the social network map and solves the problem of low efficiency during manual construction.

[0008] Optionally, the first target data is processed to obtain multiple network relationship information, specifically including: obtaining a second user, the second user being any user on the target social software who has established a first preset relationship with the first user; obtaining second target data from the first target data, the second target data being interaction data between the first user and the second user; determining a target value based on the second target data, the target value including a target duration value and a target frequency value; determining an intimacy level based on the target value, and determining the intimacy level as the network relationship information.

[0009] By adopting the above technical solution, a second user who has established a first preset relationship with the first user is obtained, and the interaction data between the first user and the second user is extracted, and the interaction data is converted into a target value, the target value includes a target duration value and a target frequency value, and the intimacy level is determined based on the target value, and the intimacy level is used as a part of the network relationship information, so as to subsequently determine the position of the second user in the target social network relationship map according to the intimacy level.

[0010] Optionally, the intimacy level is determined according to the target value, and the intimacy level includes a first intimacy level, a second intimacy level and a third intimacy level; specifically including: judging whether the target value is less than or equal to a preset first threshold; when the target value is less than or equal to the preset first threshold, confirming that the second user corresponds to the first intimacy level, and the first intimacy level is low; when the target value is greater than the preset first threshold, judging whether the target value is less than or equal to the preset second threshold; when the target value is less than or equal to the preset second threshold, confirming that the second user corresponds to the second intimacy level, and the second intimacy level is intermediate; when the target value is greater than the preset second threshold, confirming that the second user corresponds to the third intimacy level, and the third intimacy level is high.

[0011] By adopting the above technical solution, when determining the intimacy level according to the target value, by setting different thresholds, the intimacy level between users can be accurately divided into low, medium and high levels. This classification method enables the first user to clearly understand the corresponding position of the second user in the social network relationship map. This visual display method helps to improve the user experience.

[0012] Optionally, multiple network relationship information are constructed to obtain a target social network relationship map, specifically including: obtaining the intimacy level corresponding to the second user, determining the display area of ​​the second user according to the intimacy level, and constructing the target social network relationship map according to the display area.

[0013] By adopting the above technical solution, the display area is determined according to the intimacy level, and the target social network relationship map can intuitively display the social relationship between users. Users with different intimacy levels will be placed in different areas in the target social network relationship map, so that the first user can see at a glance the position of the second user in the target social network relationship map. By distinguishing the display areas of users with different intimacy levels, the confusion of the target social network relationship map can be reduced, and the user's social experience can be improved.

[0014] Optionally, the first target data is processed to obtain multiple network relationship information; specifically including: obtaining a third user, the third user being a user who establishes a second preset relationship with the first user on the target social software; extracting a target keyword from the first target data, the target keyword being a target word between the first user and the third user; obtaining multiple data types, calculating the similarity between the target keyword and each data type in turn to obtain multiple similarity values; obtaining a first similarity value, the first similarity value being a similarity value calculated between the first target data type and the target keyword, the first target data type being any one of the multiple data types; determining a second target data type corresponding to the third user according to the first similarity value, and determining the second target data type as the network relationship information.

[0015] By adopting the above technical solution, the target keywords between the third user and the first user are extracted, and the similarity between the target keywords and different data types is calculated to obtain multiple similarity values. Based on the calculated first similarity value, the data type that is most closely related to the third user can be determined, that is, the second target data type. According to the similarity value, the second user can be quickly classified into the second target data type, thereby greatly improving data processing efficiency.

[0016] Optionally, determining the second target data type corresponding to the third user based on the first similarity value specifically includes: sorting multiple similarity values ​​from large to small to obtain a sorting result; obtaining the similarity value corresponding to the first value in the sorting result to obtain a second similarity value; determining the second target data type based on the second similarity value, determining the second target data type corresponding to the third user, the second similarity value being a value calculated between the target keyword and the second target data type.

[0017] By adopting the above technical solution, multiple similarity values ​​are sorted to obtain a sorting result, and the highest similarity value in the sorting result is selected as the second similarity value, so that the data type that best matches the target keyword can be accurately identified, the second target data type is determined according to the second similarity value, the second target data type corresponding to the third user is determined, and then the social network relationship map corresponding to the second target data type is constructed, so that the first user can view the social network relationship map corresponding to the second target data type.

[0018] Optionally, the first target data is processed to obtain multiple network relationship information; specifically including: obtaining a fourth user from the target social software, and determining preset tag information corresponding to the target social software; determining a third target data type based on the preset tag information, confirming to add the fourth user to the third target data type, determining the third target data type as network relationship information, and constructing a target social network relationship map based on the third target data type.

[0019] By adopting the above technical solution, the fourth user is obtained from the target social software, the preset tag information corresponding to the target social software is determined, the third target data type is determined according to the preset tag information, the fourth user is added to the third target data type, and the user is classified into data types according to the preset tag information. This can simplify the process of analyzing the first user, and construct a target social network relationship map according to the third target data type, which can improve the accuracy and completeness of the social network relationship map and greatly improve the construction efficiency of the target social network relationship map.

[0020] In a second aspect of the present application, a device for constructing a social network relationship graph is provided, the device is a server, and the server includes an acquisition unit, a processing unit and a display unit; the acquisition unit determines the target social software in response to a click operation of a first user; the processing unit determines whether the target social software is authorized; if the target social software is authorized, the target account information is obtained, and the target account information is the account information registered and logged in on the target social software; it is determined whether the target account information is consistent with the personal information, and the personal information is the identity information corresponding to the first user; when the target account information is consistent with the personal information, it is confirmed that the first target data is obtained from the target social software; the first target data is processed to obtain multiple network relationship information; the display unit constructs the multiple network relationship information to obtain a target social network relationship graph, and displays the target social network graph to the first user, so that the first user can view the target social network graph corresponding to the target social software.

[0021] Optionally, the acquisition unit is used to acquire a second user, where the second user is any user on the target social software who has established a first preset relationship with the first user; the processing unit is used to acquire second target data from the first target data, where the second target data is interaction data between the first user and the second user; determine a target value based on the second target data, where the target value includes a target duration value and a target frequency value; determine an intimacy level based on the target value, and determine the intimacy level as network relationship information.

[0022] Optionally, the processing unit is used to determine whether the target value is less than or equal to a preset first threshold; when the target value is less than or equal to the preset first threshold, it is confirmed that the second user corresponds to the first intimacy level, and the first intimacy level is low; when the target value is greater than the preset first threshold, it is determined whether the target value is less than or equal to the preset second threshold; when the target value is less than or equal to the preset second threshold, it is confirmed that the second user corresponds to the second intimacy level, and the second intimacy level is intermediate; when the target value is greater than the preset second threshold, it is confirmed that the second user corresponds to the third intimacy level, and the third intimacy level is high.

[0023] Optionally, the acquisition unit is used to obtain the intimacy level corresponding to the second user, determine the display area of ​​the second user according to the intimacy level, and construct a target social network relationship graph according to the display area.

[0024] Optionally, the acquisition unit is used to acquire a third user, where the third user is a user who establishes a second preset relationship with the first user on the target social software; the processing unit is used to extract a target keyword from the first target data, where the target keyword is a target word between the first user and the third user; the acquisition unit is used to acquire multiple data types, and calculate the similarity between the target keyword and each data type in turn to obtain multiple similarity values; the acquisition unit is used to acquire a first similarity value, where the first similarity value is a similarity value calculated between the first target data type and the target keyword, and the first target data type is any one of the multiple data types; the processing unit is used to determine a second target data type corresponding to the third user based on the first similarity value, and determine the second target data type as network relationship information.

[0025] Optionally, the processing unit is used to sort multiple similarity values ​​from large to small to obtain a sorting result; the acquisition unit is used to obtain the similarity value corresponding to the first value in the sorting result to obtain a second similarity value; the processing unit is used to determine the second target data type based on the second similarity value, and determine the second target data type corresponding to the third user, and the second similarity value is a value calculated by the target keyword and the second target data type.

[0026] Optionally, the acquisition unit is used to obtain the fourth user from the target social software and determine the preset tag information corresponding to the target social software; the processing unit is used to determine the third target data type based on the preset tag information, confirm to add the fourth user to the third target data type, determine the third target data type as network relationship information, and construct a target social network relationship map based on the third target data type.

[0027] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.

[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.

[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. In response to a click operation of a first user, a social software for which a social network relationship map needs to be constructed is determined, and by verifying whether the target account information is consistent with the personal information, when the target account information is consistent with the personal information, it is confirmed that the first user has the authority to obtain the corresponding first target data in the target social software, and the first target data is processed to obtain multiple network relationship information, so that a target social network relationship map can be subsequently constructed through multiple network relationship information, and the data on the target social software can be automatically obtained, avoiding the tedious process of manual search and sorting of data; and then the constructed target social network relationship map is displayed to the first user, so that the first user can quickly view and analyze the target social network relationship map without waiting for the completion of the manual construction process, which significantly improves the efficiency of constructing the social network map and solves the problem of low efficiency during manual construction.

[0030] 2. Determine the display area based on the intimacy level. The target social network relationship map can intuitively display the social relationships between users. Users with different intimacy levels will be placed in different areas of the target social network relationship map, so that the first user can see at a glance the position of the second user in the target social network relationship map. By distinguishing the display areas of users with different intimacy levels, the confusion of the target social network relationship map can be reduced and the user's social experience can be improved.

[0031] 3. Obtain the fourth user from the target social software, determine the preset tag information corresponding to the target social software, determine the third target data type according to the preset tag information, add the fourth user to the third target data type, and classify the users by data type according to the preset tag information, which can simplify the first user analysis process, and construct the target social network relationship map according to the third target data type, which can improve the accuracy and completeness of the social network relationship map and greatly improve the construction efficiency of the target social network relationship map. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flowchart of a method for constructing a social network relationship graph provided in an embodiment of the present application; Figure 2 This is a schematic diagram of a first scenario of a method for constructing a social network relationship graph provided in an embodiment of the present application; Figure 3 This is a schematic diagram of a second scenario of a method for constructing a social network relationship graph provided in an embodiment of the present application; Figure 4 It is a structural schematic diagram of a device for constructing a social network relationship graph provided in an embodiment of the present application; Figure 5 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0033] Explanation of the reference numerals: 401, acquisition unit; 402, processing unit; 403, display unit; 500, electronic device; 501, processor; 502, communication bus; 503, user interface; 504, network interface; 505, memory. DETAILED DESCRIPTION

[0034] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0035] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0036] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0037] With the popularity of social media and the development of Internet technology, social data has shown an exponential growth. Constructing social network relationship graphs has become an effective means to better understand and utilize these massive data, so as to mine information with practical value. As a data structure, social network relationship graphs can clearly display the associations and interaction data between users, which is of great significance for in-depth understanding of user behavior, social relationships, and information dissemination paths.

[0038] For users, social network relationship maps help them understand their social circles more comprehensively and identify potential friends, partners or business opportunities. At the same time, by analyzing social network relationship maps, users can better understand the dissemination path and influence of information in social networks, thereby improving the efficiency and accuracy of information acquisition. However, when users currently build social network relationship maps, they usually need to manually obtain the corresponding friend information from each social software, and then aggregate the friend information to form a complete social network relationship map. However, this method takes a long time, resulting in low efficiency in building social network relationship maps.

[0039] Therefore, how to solve the problem of low efficiency in manually constructing social network relationship graphs. A method for constructing a social network relationship graph provided in an embodiment of the present application is applied to a server. The server of the present application can provide a platform for users to construct a social network relationship graph service. Figure 1 is a flow chart of a method for constructing a social network relationship graph provided in an embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S107.

[0040] S101: In response to a click operation of a first user, determining a target social software.

[0041] In the above S101, the first user needs to register the application platform first. The application platform is a platform for building a social network relationship map. The first user needs to register an account on the application platform according to personal identity information. After registration, the first user uses the account and password used during registration to log in. After login, the first user can click on the interface of the application platform to build a software list. The software list is software that can build social network relationships, that is, software that builds social network relationships includes chat software, work software, learning software, and life software. Then, the first user selects the software that needs to build a social network relationship map from the software list, that is, the first user clicks on a certain software on the software list to determine the social software that the first user needs to access, that is, the target social software. The target social software includes one or more, and the specific number is determined based on the selection of the first user, and there is no excessive limitation here.

[0042] S102: Determine whether the target social software is authorized.

[0043] In the above S102, after determining that the first user has selected the target social software, the server needs to check whether the target social software has been authorized by the first user. Authorization is usually achieved through development authorization or other similar mechanisms, allowing a third-party application to access part or all of the first user's information on the social software. In this case, the third-party application refers to the application platform of this application. If the target social software has not been authorized, the server will guide the first user to perform authorization operations, such as jumping to the authorization page of the social software, asking the first user to enter a username and password, or allowing a third-party application to access its account information.

[0044] S103: If the target social software has been authorized, then obtain the target account information, where the target account information is the account information registered and logged in on the target social software.

[0045] In the above S103, when the target social software is authorized, the server will obtain the target account information from the social software server through the application program interface or other means. The target account information is the unique identifier of the user on the target social software. The unique identifier includes the account information. The account information value includes the user's ID, nickname, avatar, gender, age and other basic information.

[0046] S104: Determine whether the target account information is consistent with the personal information, where the personal information is the identity information corresponding to the first user.

[0047] In the above S104, the server then obtains the personal information of the first user stored locally on the application platform, including the registered account number and password. Since real-name authentication is currently implemented on various social software, that is, users need to upload their personal ID number and name before they can log in to the account to perform subsequent operations, the ID number and name corresponding to the target account information can be directly obtained, and then the personal information stored by the first user on the application platform can be obtained, and the personal information also includes the ID number and name. The target account information is compared with the personal information of the first user to confirm that the target account information is indeed the first user himself, rather than the account information registered by other users. That is, when the first user wants to build a social network relationship map, it is necessary to confirm that the corresponding account on the logged-in target social software is registered by the first user himself, rather than using the identity information of others.

[0048] S105: When the target account information is consistent with the personal information, it is confirmed to obtain the first target data from the target social software.

[0049] In the above S105, when the target account information is consistent with the personal information, it is confirmed that the target account information logged in on the target social software is registered by the first user himself, and the first target data can be obtained from the target social software. The first target data is usually the social network data of the first user on the social software, and the social network data includes friend lists, chat records, dynamics, likes, comments, etc. When obtaining the first target data, it may be necessary to call the API of the social software and follow its data access rights and rules.

[0050] S106: Process the first target data to obtain a plurality of network relationship information.

[0051] In the above S106, the acquired first target data is parsed and processed to extract the network relationship information therein. The network relationship information includes the interactive relationship of the first user, etc. Since the first target data refers to the data corresponding to multiple users who have an interactive relationship with the first user, in order to distinguish the degree of intimacy between each user and the first user, the position corresponding to each user is subsequently determined based on the degree of intimacy. The position at this time refers to the position corresponding to each user in the target social network relationship map. When processing the first target data, two processing methods can be adopted. One processing method is to determine the intimacy level between the first user and other users, and determine the intimacy level corresponding to other users as network relationship information, one user corresponding to one network relationship information; another processing method is to classify the first target data in order to determine the data type corresponding to the first target data, and construct the corresponding social network relationship map according to the data type. The two processing methods are introduced in turn.

[0052] The first processing method is to process the first target data to obtain multiple network relationship information, specifically including: obtaining a second user, the second user is any user on the target social software that establishes a first preset relationship with the first user; obtaining second target data from the first target data, the second target data is the interaction data between the first user and the second user; determining a target value according to the second target data, the target value includes a target duration value and a target frequency value; determining an intimacy level according to the target value, and determining the intimacy level as network relationship information. Specifically, the second user is obtained from the target social software, the second user is any user on the target social software that establishes a first preset relationship with the first user, the first preset relationship includes a friend relationship, a family relationship, and a colleague relationship, etc., depending on the function of the target social software and the user's settings. For example, when the target social software is a learning software, the first preset relationship refers to a classmate relationship or a learning relationship; when the target social software is a work software, the first preset relationship refers to a colleague relationship or a customer relationship. In the target social software, the server will traverse all contacts or relationship lists of the first user to find users who have established a first preset relationship with the first user. Since there may be multiple second users who meet the conditions in the target social software, the server can select one or more second users according to preset rules (such as random selection), but the random selection must ensure that all second users who meet the conditions are selected to avoid omissions. The server will locate the interactive data related to the second user from the first target data that has been obtained. The interactive data includes chat records, likes, comments, shares, etc. The interactive data may contain multiple types. It is necessary to filter out the data related to the calculation of the intimacy level as the second target data according to specific business needs. Determine the target value based on the second target data. The target value includes the target duration value and the target frequency value. The target duration value is for data with timestamps such as chat records. The server can calculate the total chat duration between the first user and the second user, or the average chat duration in a specific time period, as the target duration value. The target frequency value can count the interaction frequency between the first user and the second user, such as the number of chats, likes, comments, etc. per day or per week, as the target frequency value. The intimacy level is determined based on the target value. Since the intimacy level includes the first intimacy level, the second intimacy level, and the third intimacy level, the standards for different intimacy levels can be set in advance. This standard is a value, and each value corresponds to an intimacy level. Based on the target duration value and the target frequency value, the intimacy level between the first user and the second user can be calculated. The intimacy level is then integrated with the second user to form complete network relationship information. Subsequently, the target social network relationship map is constructed based on the network relationship information.

[0053] In addition, how to judge the intimacy level corresponding to the second user according to the target value, so as to determine different display areas according to the intimacy level, and determine the intimacy level according to the target value, the intimacy level includes the first intimacy level, the second intimacy level and the third intimacy level; specifically including: judging whether the target value is less than or equal to the preset first threshold; when the target value is less than or equal to the preset first threshold, confirming that the second user corresponds to the first intimacy level, and the first intimacy level is low; when the target value is greater than the preset first threshold, judging whether the target value is less than or equal to the preset second threshold; when the target value is less than or equal to the preset second threshold, confirming that the second user corresponds to the second intimacy level, and the second intimacy level is intermediate; when the target value is greater than the preset second threshold, confirming that the second user corresponds to the third intimacy level, and the third intimacy level is high. Specifically, obtain the target value, judge whether the target value is less than or equal to the preset first threshold, the preset first threshold represents the minimum standard of the intimacy level, and the preset first threshold can be set according to the characteristics of the target social software, user groups and business needs. Since the target value includes the target duration value and the target frequency value, the preset first threshold value includes the first duration threshold value and the first frequency threshold value, that is, to determine whether the target duration value is less than or equal to the first duration threshold value, and whether the target frequency value is less than or equal to the first frequency threshold value. When the target duration value is less than or equal to the first duration threshold value, and the target frequency value is less than or equal to the first frequency threshold value, it is confirmed that the intimacy level between the second user and the second user is the first intimacy level, and the first intimacy level is low. This first intimacy level can be assigned to the second user, so that the second user's display position in the target social network relationship map can be determined later according to the first intimacy level. When the target duration value is greater than the first duration threshold value, and the target frequency value is greater than the first frequency threshold value, it means that the intimacy level between the first user and the second user has exceeded the first intimacy level, and it is necessary to enter the next round of judgment. To determine whether the target value is less than or equal to a preset second threshold, the server will also set a preset second threshold, which represents a medium standard for the intimacy level. The target value is compared with the preset second threshold, which includes a second duration threshold and a second frequency threshold, that is, to determine whether the target duration value is less than or equal to the second duration threshold, and the target frequency value is less than or equal to the second frequency threshold. When the target value is less than or equal to the preset second threshold, that is, when the target duration value is less than or equal to the second duration threshold, and the target frequency value is less than or equal to the second frequency threshold, it is confirmed that the intimacy level between the second user and the second user is the second intimacy level, and the second intimacy level is medium. The second intimacy level can be assigned to the second user so that the second user's display position in the target social network relationship map can be determined later according to the second intimacy level.When the target value is greater than the preset second threshold, that is, when the target duration value is greater than the second duration threshold, and the target frequency value is greater than the second frequency threshold, it is confirmed that the intimacy level between the second user and the first user is the third intimacy level, and the third intimacy level is high. The high level indicates that the intimacy is very high. This third intimacy level can be assigned to the second user so that the second user's display position in the target social network relationship map can be determined according to the third intimacy level. By setting different thresholds as described above, the user's intimacy is quantified into different levels, making the display of the social network relationship map more intuitive and easy to understand. In addition to determining the intimacy level of the second user by the target value, the intimacy level can also be determined according to the geographical location corresponding to each user. The geographical location can be determined according to the mobile phone number, and the home location corresponding to the mobile phone number is obtained, and the geographical location is determined based on the home location. The preset geographical location corresponding to the first user is obtained, and then the geographical location corresponding to the second user is obtained. The preset geographical location and the geographical location are calculated to obtain the target distance, which represents the distance between the first user and the second user. It is determined whether the target distance is less than the preset distance. When the target distance is less than the preset distance, it is confirmed that the second user corresponds to the third intimacy level, and the third intimacy level corresponds to the high level. When the target distance is equal to the preset distance, it is confirmed that the second user corresponds to the second intimacy level, and the second intimacy level corresponds to the medium level. When the target distance is greater than the preset distance, it is confirmed that the second user corresponds to the first intimacy level, and the first intimacy level corresponds to the low level. It can be understood that the closer the geographical locations between the two users are, the higher the corresponding intimacy level is, and the farther the geographical locations between the two users are, the lower the corresponding intimacy level is.

[0054] Furthermore, after determining the intimacy level of the second user, how to determine the display area according to the intimacy level, and construct the target social network relationship map, construct multiple network relationship information, and obtain the target social network relationship map, specifically including: obtaining the intimacy level corresponding to the second user, determining the display area of ​​the second user according to the intimacy level, and constructing the target social network relationship map according to the display area. Specifically, according to the previous steps, a target value can be determined, and then the intimacy level can be determined according to the target value, and the target value can be compared with a preset first threshold or a preset second threshold, and the intimacy level can be determined according to the comparison result. Then, the display area of ​​the second user is determined according to the intimacy level. According to the design of the social network relationship map, different display areas corresponding to different intimacy levels can be pre-defined. For example, if Figure 2As shown, M represents the first user, and users with low intimacy are located at the edge of the graph, a represents low; users with medium intimacy are located in the middle area of ​​the graph, b represents medium; and users with high intimacy may be located in the center or prominent position of the graph, c represents high. Determine the intimacy level of the second user, match the intimacy level with the predefined display area, and determine the specific position of the second user in the picture. It can also be understood that the user corresponding to the higher intimacy level of the first user is closer to the first user, and the user corresponding to the lower intimacy level of the first user is farther away from the first user. Initialize the structure of the social network relationship graph, including nodes (representing users) and edges (representing the relationship between users). Add edges to the relationship between the first user and the second user (such as friends, attention, etc.) in the graph to connect the two nodes. Then, according to the display area determined by the intimacy level, adjust the position of the nodes in the graph so that the second user is placed in the corresponding position according to his intimacy level. Then display the constructed target social network relationship graph to the first user to help the first user intuitively understand and manage his social network.

[0055] The second processing method, the method of determining the data type is divided into two cases. The first case: obtain the keywords between the first user and the third user, calculate the similarity values ​​between the keywords and each data type, compare multiple similarity values, select the largest similarity value, and then obtain the second target data type corresponding to the largest similarity value, and determine that the third user corresponds to the second target data type. The second case: first obtain the fourth user from the target social software, then obtain the attributes corresponding to the target social software, determine the third target data type according to the attributes, and add the fourth user to the third target data type to determine that the fourth user corresponds to the third target data type. The following will introduce the two cases in turn.

[0056] In the first case of determining the data type, the first target data is processed to obtain multiple network relationship information; specifically, the third user is obtained, and the third user is a user who establishes a second preset relationship with the first user on the target social software; the target keyword is extracted from the first target data, and the target keyword is the target word between the first user and the third user; multiple data types are obtained, and the target keyword is calculated with each data type in turn to obtain multiple similarity values; the first similarity value is obtained, and the first similarity value is the similarity value calculated between the first target data type and the target keyword, and the first target data type is any one of the multiple data types; the second target data type corresponding to the third user is determined according to the first similarity value, and the second target data type is determined as network relationship information. Specifically, the third user is obtained from the target social software, and the third user is a user who establishes a second preset relationship with the first user on the target social software. The second preset relationship is a certain specific relationship defined on the target social software, such as colleagues, alumni, common interest groups, etc. In the target social software, all contacts or relationship lists of the first user are traversed to find the user who establishes a second preset relationship with the first user, that is, the third user. The part related to the third user is found in the first target data, including chat records, dynamic updates, and comments. Natural language processing technology (such as word segmentation, part-of-speech tagging, named entity recognition, etc.) can be used to extract words that frequently appear or have special meanings when communicating with the third user from these data to build a keyword database, and the target keyword is any word in the keyword database. When building the keyword database, it can also be classified according to the data theme, such as finance, society, politics, economy, entertainment, etc. The databases of different classifications are aggregated to obtain a total keyword database. In order to facilitate the classification of the social network relationship of the first user, multiple data types are defined according to the interaction characteristics of the first user and the third user. The data types include entertainment type, learning type, life type and work type. Obtain multiple data types, calculate the similarity between the target keyword and each data type in turn, and obtain multiple similarity values, one similarity value is obtained by calculating the similarity between a data type and the target keyword. Then prepare a certain number of data samples for each data type, and the data samples can reflect the characteristics of the data type. The similarity calculation between the extracted target keyword and the samples of each data type can be achieved in a variety of ways, such as cosine similarity, Jaccard similarity, edit distance, etc. The selection of a specific method depends on the characteristics of the data type and the target keyword. A first target data type is selected from a plurality of data types, and the selection may be based on business requirements, data availability or other considerations. A similarity value between the first target data type and the target keyword is calculated, namely, a first similarity value.If it is determined that the target keyword is the most matched to the first target data type, the second target data type is determined according to the first similarity value. At this time, the second target data type serves as network relationship information, that is, the third user corresponds to the second target data type, and the third user is added to the second target data type so that a target social network relationship graph can be subsequently constructed according to the second target data type, that is, one target data type corresponds to the construction of one target social network relationship graph.

[0057] In addition, the second target data type corresponding to the third user is determined according to the first similarity value, specifically including: sorting multiple similarity values ​​from large to small to obtain a sorting result; obtaining the similarity value corresponding to the first value in the sorting result to obtain a second similarity value; determining the second target data type according to the second similarity value, and determining the second target data type corresponding to the third user, the second similarity value is a value calculated by calculating the target keyword and the second target data type. Specifically, after calculating the similarity between the target keyword and each data type, multiple similarity values ​​are obtained, and then the multiple similarity values ​​are sorted from large to small to obtain a sorting result, and the value with the highest similarity in the sorting result is located at the top of the list. Obtain the similarity value corresponding to the first value in the sorting result to obtain the second similarity value, and the second similarity value is the one with the highest similarity value in the sorting result. Then determine the second target data type according to the second similarity value, and obtain the second target data type with the highest similarity to the target keyword among all data types, that is, the second target data type corresponding to the second similarity value. It is determined that the third user is the most compatible with the second target data type. Since the target keyword is extracted from the communication between the first user and the third user, the second target data type can be associated with the third user, thereby determining that the third user belongs to the second target data type. After determining the second target data type corresponding to the third user, a target social network relationship graph is constructed based on the second target data type, and then all users in the target social network relationship graph correspond to the second target data type.

[0058] For example, target keywords are extracted from the third user W and the first user. The target keyword is "copying calligraphy". Multiple data types include learning type, entertainment type, work type and life type. The similarity between the target keyword and the samples of each data type is calculated in turn. The similarity value between the target keyword and the learning type is 70%, the similarity value between the target keyword and the entertainment type is 30%, the similarity value between the target keyword and the work type is 40%, and the similarity value between the target keyword and the life type is 45%. The multiple similarity values ​​are sorted from large to small to determine the similarity value of 70% corresponding to the first place in the sorting result. That is, the second similarity value is 70%, and the second target data type corresponding to the second similarity value is obtained. At this time, the second target data type is the learning type, so it is determined that the third user W belongs to the second target data type, that is, the third user W belongs to the target social network relationship map corresponding to the learning type. Figure 3 As shown, A represents the learning type, B represents the entertainment type, C represents the work type, and D represents the life type. The third user W is classified into the data type corresponding to A, M represents the first user, and the arrow indicates the user who has an interactive relationship with the first user, and then a social network relationship graph including user W and the first user M is constructed. If the entertainment type B includes user T and user Y, then a social network relationship graph including user T, user Y and the first user M is constructed. If the life type D includes user H, then a social network relationship graph including user H and the first user M is constructed. If the work type C includes user K and user E, then a social network relationship graph including user K, user E and the first user M is constructed.

[0059] The second method of determining the data type is to process the first target data to obtain multiple network relationship information; specifically, the method includes: obtaining the fourth user from the target social software, determining the preset tag information corresponding to the target social software; determining the third target data type according to the preset tag information, confirming that the fourth user is added to the third target data type, determining the third target data type as network relationship information, and constructing the target social network relationship map based on the third target data type. Specifically, to obtain the fourth user from the target social software, it is necessary to clarify which target social software the fourth user is obtained from, so as to facilitate the subsequent determination of the data type corresponding to the fourth user. Obtain the basic information of the fourth user from the target social software. Then determine the preset tag information corresponding to the target social software, that is, after determining that the fourth user is obtained from the target social software, it is necessary to determine the preset tag information of the target social software according to the function, characteristics and user group of the target social software. The preset tag information represents the attributes of the target social software. Then determine the third target data type according to the preset tag information, confirm that the fourth user is added to the third target data type, and if the third target data type already exists, directly add the fourth user to the third target data type. If the third target data type does not exist, it is necessary to create a new data type and add the fourth user to the type. The third target data type is determined as network relationship information, and a target social network relationship map is constructed based on the third data type. By constructing social network relationship maps corresponding to different data types, the first user can find corresponding friends from the data type corresponding to the actual needs according to actual needs.

[0060] For example, the function of software A is data query, the feature is word query, and the user group is a student group or a working group, that is, the preset label information corresponding to software A is English learning software. Then determine the third target data type according to the preset label information, that is, determine the third target data type according to the preset label information. The data type can be set to learning type, work type, entertainment type and life type. The data type can also be set based on actual conditions. This is just an example. The preset label information is English learning software, and English learning software corresponds to the learning type, that is, the third target data type is the learning type at this time. Then add the fourth user to the learning type, and construct a social network relationship map corresponding to the learning type.

[0061] S107: constructing multiple network relationship information to obtain a target social network relationship map, and displaying the target social network map to the first user so that the first user can view the target social network map corresponding to the target social software.

[0062] In the above S107, one network relationship information corresponds to one user, and multiple network relationship information are integrated and constructed to generate a target social network relationship map. The target social network relationship map is a visual display form that can intuitively reflect the social network structure and relationship on the social software. Obtain each friend of the first user on the target social software, and then construct a social network relationship map centered on the first user. If the target social software includes three, the users of the three target social software that have an interactive relationship with the first user can be obtained, and then an overall social network relationship map can be constructed. After the social network relationship map is constructed, the display position of each user in the social network relationship map is determined according to the intimacy level between the first user and other users. The first target data obtained can also be analyzed to determine the data type, and different social network relationship maps can be constructed according to different data types. The constructed target social network relationship map is displayed to the first user, and the display method can be a web page, a mobile application interface, a chart, etc., depending on the application scenario and user needs. The first user can also view and analyze different parts and details in the target social network relationship map through interactive elements on the interface (such as zooming, dragging, clicking, etc.).

[0063] Through the above method, according to the click operation of the first user, data is obtained and processed from the target social software, a target social network relationship map is constructed, and displayed to the first user, helping the first user to better understand his or her social network structure and relationships.

[0064] The present application also provides a device for constructing a social network relationship graph. Figure 4 is a schematic diagram of a structure of a device for constructing a social network relationship graph provided in an embodiment of the present application, with reference to Figure 4 The device is a server, and the server includes an acquisition unit 401, a processing unit 402 and a display unit 403.

[0065] The acquisition unit 401 determines a target social software in response to a click operation of a first user.

[0066] Processing unit 402 determines whether the target social software is authorized; if the target social software is authorized, obtains target account information, which is the account information registered and logged in on the target social software; determines whether the target account information is consistent with the personal information, which is the identity information corresponding to the first user; when the target account information is consistent with the personal information, confirms to obtain the first target data from the target social software; processes the first target data to obtain multiple network relationship information.

[0067] The display unit 403 constructs multiple network relationship information to obtain a target social network relationship map, and displays the target social network map to the first user so that the first user can view the target social network map corresponding to the target social software.

[0068] In a possible implementation, the acquisition unit 401 is used to acquire a second user, where the second user is any user on the target social software who has established a first preset relationship with the first user; the processing unit 402 is used to acquire second target data from the first target data, where the second target data is interaction data between the first user and the second user; a target value is determined based on the second target data, where the target value includes a target duration value and a target frequency value; an intimacy level is determined based on the target value, and the intimacy level is determined as network relationship information.

[0069] In one possible implementation, the processing unit 402 is used to determine whether the target value is less than or equal to a preset first threshold; when the target value is less than or equal to the preset first threshold, it is confirmed that the second user corresponds to the first intimacy level, and the first intimacy level is low; when the target value is greater than the preset first threshold, it is determined whether the target value is less than or equal to the preset second threshold; when the target value is less than or equal to the preset second threshold, it is confirmed that the second user corresponds to the second intimacy level, and the second intimacy level is intermediate; when the target value is greater than the preset second threshold, it is confirmed that the second user corresponds to the third intimacy level, and the third intimacy level is high.

[0070] In a possible implementation, the acquisition unit 401 is used to acquire the intimacy level corresponding to the second user, determine the display area of ​​the second user according to the intimacy level, and construct a target social network relationship graph according to the display area.

[0071] In a possible implementation, the acquisition unit 401 is used to acquire a third user, where the third user is a user who has established a second preset relationship with the first user on the target social software; the processing unit 402 is used to extract a target keyword from the first target data, where the target keyword is a target word between the first user and the third user; the acquisition unit 401 is used to acquire multiple data types, and calculate the similarity between the target keyword and each data type in turn to obtain multiple similarity values; the acquisition unit 401 is used to acquire a first similarity value, where the first similarity value is a similarity value calculated between the first target data type and the target keyword, and the first target data type is any one of the multiple data types; the processing unit 402 is used to determine the second target data type corresponding to the third user based on the first similarity value, and determine the second target data type as network relationship information.

[0072] In a possible implementation, the processing unit 402 is used to sort multiple similarity values ​​from large to small to obtain a sorting result; the acquisition unit 401 is used to obtain the similarity value corresponding to the first position in the sorting result to obtain a second similarity value; the processing unit 402 is used to determine the second target data type based on the second similarity value, and determine the second target data type corresponding to the third user, and the second similarity value is a value calculated by the target keyword and the second target data type.

[0073] In a possible implementation, the acquisition unit 401 is used to acquire the fourth user from the target social software and determine the preset tag information corresponding to the target social software; the processing unit 402 is used to determine the third target data type based on the preset tag information, confirm to add the fourth user to the third target data type, determine the third target data type as network relationship information, and construct a target social network relationship map based on the third target data type.

[0074] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0075] The present application also discloses an electronic device. Figure 5 , Figure 5 The electronic device 500 may include: at least one processor 501 , at least one network interface 504 , a user interface 503 , a memory 505 , and at least one communication bus 502 .

[0076] The communication bus 502 is used to realize the connection and communication between these components.

[0077] The user interface 503 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 503 may also include a standard wired interface and a wireless interface.

[0078] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0079] Among them, the processor 501 may include one or more processing cores. The processor 501 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 505, and calling data stored in the memory 505. Optionally, the processor 501 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 501 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 501, and it can be implemented separately through a chip.

[0080] Among them, the memory 505 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 505 includes a non-transitory computer-readable storage medium. The memory 505 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 505 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 505 can also be optionally at least one storage device located away from the aforementioned processor 501.

[0081] like Figure 5 As shown, the memory 505 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for constructing a social network relationship graph.

[0082] exist Figure 5In the electronic device 500 shown, the user interface 503 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 501 can be used to call the application for building a social network relationship graph stored in the memory 505. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0083] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0084] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0085] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0086] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0087] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0088] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0089] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure.

Claims

1. A method for constructing a social network relationship graph, characterized in that: Applied in a server, the method comprises: In response to a click operation by the first user, determining a target social software; Determine whether the target social software is authorized; If the target social software has been authorized, then obtaining target account information, where the target account information is the account information registered and logged in on the target social software; Determining whether the target account information is consistent with personal information, where the personal information is identity information corresponding to the first user; When the target account information is consistent with the personal information, it is confirmed to obtain the first target data from the target social software; Processing the first target data to obtain a plurality of network relationship information; The plurality of network relationship information are constructed to obtain a target social network relationship graph, and the target social network graph is displayed to the first user so that the first user can view the target social network graph corresponding to the target social software.

2. The method according to claim 1, characterized in that The processing of the first target data to obtain a plurality of network relationship information specifically includes: Acquire a second user, where the second user is any user on the target social software who has established a first preset relationship with the first user; Acquire second target data from the first target data, where the second target data is interaction data between the first user and the second user; Determine a target value according to the second target data, wherein the target value includes a target duration value and a target frequency value; An intimacy level is determined according to the target value, and the intimacy level is determined as the network relationship information.

3. The method according to claim 2, characterized in that The intimacy level is determined according to the target value, and the intimacy level includes a first intimacy level, a second intimacy level, and a third intimacy level; specifically includes: Determining whether the target value is less than or equal to a preset first threshold; When the target value is less than or equal to the preset first threshold, it is confirmed that the second user corresponds to the first intimacy level, and the first intimacy level is low; When the target value is greater than the preset first threshold, determining whether the target value is less than or equal to a preset second threshold; When the target value is less than or equal to the preset second threshold, it is confirmed that the second user corresponds to the second intimacy level, and the second intimacy level is medium; When the target value is greater than the preset second threshold, it is confirmed that the second user corresponds to the third intimacy level, and the third intimacy level is high.

4. The method according to claim 3, characterized in that: The step of constructing the plurality of network relationship information to obtain a target social network relationship graph specifically includes: The intimacy level corresponding to the second user is obtained, a display area of ​​the second user is determined according to the intimacy level, and the target social network relationship graph is constructed according to the display area.

5. The method according to claim 1, characterized in that The first target data is processed to obtain a plurality of network relationship information; Specifically include: Acquire a third user, where the third user is a user on the target social software who has established a second preset relationship with the first user; Extracting a target keyword from the first target data, the target keyword being a target word between the first user and the third user; Acquire multiple data types, and calculate similarity between the target keyword and each of the data types in turn to obtain multiple similarity values; Obtaining a first similarity value, where the first similarity value is a similarity value calculated between the first target data type and the target keyword, and the first target data type is any one of the multiple data types; A second target data type corresponding to the third user is determined according to the first similarity value, and the second target data type is determined as the network relationship information.

6. The method according to claim 5, characterized in that The determining, according to the first similarity value, the second target data type corresponding to the third user specifically includes: Sorting the plurality of similarity values ​​from large to small to obtain a sorting result; Obtaining a similarity value corresponding to the first position in the sorting result to obtain a second similarity value; The second target data type is determined according to the second similarity value, and it is determined that the third user corresponds to the second target data type, wherein the second similarity value is a value obtained by calculating the target keyword and the second target data type.

7. The method according to claim 1, characterized in that The first target data is processed to obtain a plurality of network relationship information; Specifically include: Acquire a fourth user from the target social software, and determine preset tag information corresponding to the target social software; Determine a third target data type according to the preset tag information, confirm to add the fourth user to the third target data type, determine the third target data type as the network relationship information, and construct the target social network relationship graph based on the third target data type.

8. A device for constructing a social network relationship graph, characterized in that: The device is a server, and the server comprises an acquisition unit (401), a processing unit (402) and a display unit (403); The acquisition unit (401) determines the target social software in response to a click operation of the first user; The processing unit (402) determines whether the target social software has been authorized; if the target social software has been authorized, obtains target account information, the target account information is the account information registered and logged in on the target social software; determines whether the target account information is consistent with personal information, the personal information is the identity information corresponding to the first user; When the target account information is consistent with the personal information, it is confirmed to obtain the first target data from the target social software; Processing the first target data to obtain a plurality of network relationship information; The display unit (403) constructs the plurality of network relationship information to obtain a target social network relationship graph, and displays the target social network graph to the first user so that the first user can view the target social network graph corresponding to the target social software.

9. An electronic device, characterized in that: The electronic device (500) comprises a processor (501), a memory (505), a user interface (503) and a network interface (504), wherein the memory (505) is used to store instructions, the user interface (503) and the network interface (504) are used to communicate with other devices, and the processor (501) is used to execute the instructions stored in the memory (505) so that the electronic device (500) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

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