Method and electronic equipment for providing social media network account operation management service

Abstract

The embodiment of the invention discloses a method for providing social media network account operation management service and electronic equipment, and the method comprises the steps: constructing a social media network SNS account matrix system of a target subject, the account matrix system comprises a main account registered by the target subject in an SNS network, the plurality of country / region accounts are registered for a plurality of different countries / regions respectively, the at least one sub-account is associated with each country / region account, and the sub-accounts have respective account portrait positioning in the aspect of specific subdivided crowds, industries and / or commodity categories; performing automatic content generation and release through an artificial intelligence AI large model according to a content release strategy corresponding to an account in the account matrix system; wherein the content publishing strategy corresponding to the sub-account is related to account portrait positioning of the account. According to the embodiment of the invention, the account operation effect in a cross-border scene can be improved, and the operation cost is reduced.

Description

Technical Field

[0001] The present application relates to the field of information processing technology, and in particular to a method and electronic device for providing social media network account operation and management services. Background Art

[0002] Social network service (SNS) operation has become an indispensable part of modern enterprise marketing strategy. Enterprises can improve brand exposure, enhance user interaction rate and increase website traffic by managing and optimizing their online accounts through social media platforms and publishing online posts and other content. In the current highly competitive market environment, a successful SNS operation strategy can not only win more consumer attention for enterprises, but also enhance the competitive advantage of brands.

[0003] The core of SNS operation is to enhance brand influence, increase user participation and guide traffic through effective content management and user interaction. With the rapid development of social media, enterprises pay more and more attention to SNS operation, which provides a broad development space and market demand for the innovation of related technologies and methods.

[0004] In order to meet the SNS operation needs of enterprises, some products or tools can provide enterprises with comprehensive social media content management functions, such as title optimization, potential hot topic lists, hot post content rewriting, copywriting polishing and optimal publishing time suggestions, to help enterprises improve the quality of social media interaction, or help enterprises increase the exposure and interaction of tweets, etc.

[0005] However, in the process of SNS operation, user interaction usually shows obvious localization characteristics. If an enterprise or platform only faces users in a certain country, since the enterprise is usually very familiar with the culture of the country, users may also be very familiar with such enterprises or platforms, and the operators of the enterprise or platform usually know very clearly which content is easy to attract users' attention, etc. Therefore, on this basis, it is usually feasible to combine and use the above-mentioned content optimization related products or tools to improve the content quality. However, some enterprises or platforms may be involved in cross-border trade. At this time, they may need to operate cross-border SNS for users in multiple countries or regions. Different countries / regions have different cultures, and users in different countries / regions may pay attention to different hot topics. Users in other countries / regions may not be particularly familiar with specific enterprises / platforms. In addition, there are differences in language, time difference, etc. It can be seen that the difficulty of SNS operation in cross-border scenarios will be quite large. In the existing technology, enterprises / platforms usually need to configure local operators in different countries / regions. Such operators need to have a good understanding of the local cultural background, have a keen insight into hot current events, and have good content production capabilities, etc., and the operating costs will be very high. Summary of the invention

[0006] The present application provides a method and electronic device for providing social media network account operation and management services, which can improve account operation effects in cross-border scenarios and reduce operating costs.

[0007] This application provides the following solutions:

[0008] A method for providing social media network account operation management services, applied to an account operation management service system, the method comprising:

[0009] Determine a social media network SNS account matrix system of the target subject, wherein the account matrix system includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, wherein the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-accounts have respective account portrait positioning in terms of specific segments of the population, industries and / or commodity categories;

[0010] The artificial intelligence AI big model is used to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system; wherein the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

[0011] Wherein, when the content is generated for the sub-account by using the AI ​​big model, it includes:

[0012] Collect hotspot data;

[0013] The hot data is understood through the AI ​​big model for decision-making to determine the appropriate content type, as well as the appropriate country / region, target population, industry and / or product category, and at least one target sub-account related to the target country / region, target population, industry and / or product category is determined;

[0014] The AI ​​big model pre-trained for the target sub-account generates the corresponding type of content for the target sub-account, and determines the publishing time according to the corresponding publishing time strategy.

[0015] Among them, the target entities include cross-border commodity information service platforms;

[0016] The content types include product recommendation categories;

[0017] The method further comprises:

[0018] Determining a target commodity related to the hot data and related display materials of the target commodity from the commodity information service platform;

[0019] The relevant display materials of the target product are provided to the AI ​​big model trained for the target sub-account, so as to generate text content related to product recommendation according to the hot data, and assemble them with the display materials into content to be published of the product recommendation category.

[0020] Wherein, when the content is generated for the sub-account by using the AI ​​big model, it also includes:

[0021] After generating the corresponding type of content for the target sub-account, the generated content is adapted to the SNS network in terms of content style, format, specifications, required interactive elements and / or user preferences according to the SNS network corresponding to the target sub-account.

[0022] Wherein, when performing the adaptation process, if the SNS network supports multiple different content formats, the generated content is rewritten in multiple ways to generate content corresponding to the multiple content formats, and the content is published in different content formats respectively.

[0023] Among them, it also includes:

[0024] The content publishing strategy corresponding to the sub-account is updated according to the user's interactive feedback on the content published in the account.

[0025] Among them, it also includes:

[0026] The AI ​​big model is used to carry out collaborative interactive processing between different accounts in the account matrix system.

[0027] The collaborative interaction between different accounts in the account matrix system includes:

[0028] The quality of the content generated by the AI ​​big model for the sub-account is judged. If it meets the preset conditions, the country / region account of the country / region to which the sub-account belongs and / or the main account are mentioned in the generated content to achieve interaction between the sub-account and the country / region account and / or the main account.

[0029] The collaborative interaction between different accounts in the account matrix system includes:

[0030] Part of the content published by the country / region account of the country / region to which it belongs is forwarded through the sub-account.

[0031] The collaborative interaction between different accounts in the account matrix system includes:

[0032] Sub-accounts with the same or related account profiles follow each other and / or forward each other’s content.

[0033] Among them, it also includes:

[0034] After an account in the account matrix system receives a comment or private message from a user regarding a published content, the account uses the AI ​​big model to generate a reply to the comment or private message.

[0035] Among them, it also includes:

[0036] Through the sub-accounts in the account matrix system, well-known accounts outside the system in the corresponding industry or field are followed, and after the well-known accounts outside the system publish content, the AI ​​big model is used to generate comment content for the published content.

[0037] Among them, it also includes:

[0038] By setting up a keyword and / or theme monitoring mechanism, hot topics and / or discussion trend contents in the SNS network are captured and analyzed in real time, and sub-accounts related to the hot topics and / or discussion trend contents in the account matrix system are determined, and content commenting on the hot topics and / or discussion trend contents by the sub-account is generated through the AI ​​big model.

[0039] A method for processing SNS account information, comprising:

[0040] Receiving account configuration information submitted for a target subject through a target interface, the account configuration information includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-accounts have respective account portrait positioning for specific segments of the population, industries and / or commodity categories;

[0041] An SNS account matrix system of the target entity is constructed according to the account configuration information, so as to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system through the AI ​​big model; wherein the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

[0042] Among them, the AI ​​big model is also used for collaborative interactive processing between different accounts.

[0043] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of any of the methods described above.

[0044] An electronic device, comprising:

[0045] one or more processors; and

[0046] A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of any of the methods described above.

[0047] A computer program product comprises a computer program / computer executable instructions, wherein the computer program / computer executable instructions implement the steps of any of the aforementioned methods when executed by a processor in an electronic device.

[0048] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0049] Through the embodiment of the present application, account operation management services can be provided for entities with cross-border account operations. Through this service, an SNS account matrix system can be constructed for specific entities. The matrix can include the main account registered by the entity in the SNS network, and can also include country / region accounts registered for multiple countries / regions. Each country / region account can also have at least one sub-account. This sub-account can be an account registered directly by the current entity in the SNS network, or it can be an account registered by other entities in the SNS network and authorized to the current entity for operation and trusteeship; wherein, this sub-account has its own account portrait positioning for specific segments of the population, industries and / or commodity categories. On the basis of constructing the above account matrix system, the artificial intelligence AI model can also be used to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system; wherein, the content publishing strategy corresponding to the sub-account can be related to the account portrait positioning of the account, so that the content, time, etc. published by the specific sub-account are all related to the specific account portrait positioning, realizing refined operations for each user group, so that the same sub-account can obtain continuous attention from the corresponding population.

[0050] In an optional implementation, the AI ​​big model can also be used to perform collaborative interaction between different accounts in the account matrix system, including mentioning the country / region account and / or main account of the country / region to which the sub-account belongs in the content generated for the sub-account; or forwarding part of the content published by the country / region account of the country / region to which the sub-account belongs through the sub-account; or following each other between sub-accounts with the same or related account portrait positioning, and / or forwarding each other's published content, etc. Through such interaction between accounts, the effect of widely displaying the brand image to users can be formed, reducing the account operation cost.

[0051] In addition, intelligent replies can be achieved through the AI ​​big model, including replies to users' comments or private messages, or intelligent replies to content posted by popular accounts in the industry. Alternatively, keywords and / or topic monitoring mechanisms can be set to capture and analyze hot topics and / or discussion trend content in the SNS network in real time, and sub-accounts related to the hot topics and / or discussion trend content in the account matrix system can be determined, and content commenting on the hot topics and / or discussion trend content with the sub-account can be generated through the AI ​​big model.

[0052] Of course, any product implementing the present application does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0054] Figure 1 It is a schematic diagram of the system architecture provided by the embodiment of the present application;

[0055] Figure 2 is a flow chart of the first method provided in an embodiment of the present application;

[0056] Figure 3 is a schematic diagram of an account matrix system provided in an embodiment of the present application;

[0057] Figure 4 is a flow chart of the second method provided in an embodiment of the present application;

[0058] Figure 5 It is a schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0060] First of all, it should be noted that in cross-border trade scenarios, both the platform (a platform that provides commodity information services, generally referred to as an e-commerce platform, etc.) and specific merchants and other corporate parties will face the problem that foreign users may not be very familiar with the platform or the company. If the platform needs to carry out certain large-scale marketing activities, or the company needs to increase the popularity of its own brand, etc., then using SNS accounts for related publicity is an important way to effectively reach consumers with relevant information, achieve more interactions with users, and then achieve traffic to the platform or specific brand stores. In the prior art, in order to achieve the above purpose, it is usually achieved by optimizing the quality of the published content to attract users. However, due to the great differences in culture in different countries / regions, if you want to carry out differentiated account operations in multiple countries and achieve the purpose of publicity, you often face huge operating costs.

[0061] In the embodiment of the present application, in order to help the relevant platform party or enterprise party to operate SNS accounts in the cross-border trade scenario, see Figure 1, can provide an account operation management service system for providing SNS operation management services for specific entities (for example, including e-commerce platforms or enterprises, etc.), that is, to help the entity realize SNS account management in the cross-border commodity trade scenario. Specifically, first, in this service, an SNS account matrix system can be created for specific platforms or enterprises, and a three-level account matrix operation system of "main account-national account-sub-account" can be established, so that the refinement of operations can be improved according to the national dimension. Sub-accounts can also have their own portrait positioning, for example, they can be oriented to a certain segmented population, industry, commodity category, etc., so that such sub-accounts can be used to target people in more vertical fields and expand the user reach of followers (commonly known as "fans", etc.). In other words, such sub-accounts can realize refined operations for each segmented population. A sub-account can only publish content that users of the segmented population want to see, rather than posting it in a divergent manner, so that each sub-account can maintain a specific group of followers (fans) (otherwise, if an account posts all content, it may lead to different groups of people liking different content of the same account, and some of them will pay less attention to the account because they may think that the account cannot be the source of information they need).

[0062] Taking a specific subject as an e-commerce platform as an example, in the above three-level account matrix operation system, the SNS main account of the platform can be determined first, and then the same platform can also be associated with multiple country / region accounts for content publishing to users in specific countries / regions. Further, multiple sub-accounts can be associated under specific country / region accounts. These sub-accounts can be multiple "small accounts" registered by the platform itself, or, in the embodiment of the present application, they can also be SNS accounts registered by some merchants, but they can be authorized to the platform for operation, etc. In other words, the sub-account can be an SNS account registered by the current subject itself, or it can be an SNS account registered by other subjects but authorized to the current subject. Among them, whether the current subject registers by itself, or other subjects register and authorize the current subject to operate, these sub-accounts can have their own portrait positioning, that is, a specific sub-account can be a segmented group of people in a vertical field, or a specific industry and / or a specific commodity category, and accordingly, the content published by these sub-accounts can also correspond to their portrait positioning.

[0063] Among them, since there may be multiple SNS networks, the same subject may also have multiple main accounts, corresponding to multiple different SNS networks. Correspondingly, the same subject may also have multiple intermediate accounts in the same country / region, corresponding to different SNS networks. The sub-accounts are similar. For the same segmented population or the same industry, category, etc., they can correspond to different sub-accounts in different SNS networks. This makes the number of accounts of the same subject in the above three-level account matrix operation system very large, and in order to achieve more refined operations, the content and time of different accounts may need to be different. Therefore, if the existing technology is still used to edit the content to be published by each account through specific operators, the workload is huge, and it may even be an impossible task.

[0064] Therefore, in the embodiment of the present application, on the basis of the above-mentioned three-level account matrix system, a solution based on an AI (Artificial Intelligence) big model is also proposed to realize the automated operation of the above-mentioned account. Among them, the so-called AI big model usually refers to a deep learning model containing a large number of parameters. Due to its large scale, this AI big model can store and process a large amount of information, thereby achieving higher performance in various tasks. Therefore, the intelligent account operation in the embodiment of the present application can be realized by relying on the powerful natural language text understanding, logical thinking and content generation capabilities of the pre-trained AI big model. Specifically, the AI ​​big model can be used to automatically generate and publish content according to the content publishing strategy corresponding to the specific account. This content publishing strategy can be related to the account portrait positioning of the specific account, that is, it is necessary to generate content suitable for different portrait positioning for different accounts, and it can also realize the automated processing of publishing time, language, etc. according to the country / region to which the specific account belongs. It should be noted here that, in specific implementation, the AI ​​big model can mainly generate specific content for sub-accounts, while the content published by the main account, country / region account, etc. usually has certain characteristics such as authority, or represents the image of a specific platform or brand in a specific country / region, etc. The specific content published needs to be more cautious, and the number of main accounts and country / region accounts is not particularly large. Therefore, it can be generated manually, or it can be published after manual review based on AI generation, etc.

[0065] In addition, the AI ​​big model can also be used to manage the collaborative relationship between different accounts to achieve mutual traffic diversion between different accounts. For example, after the AI ​​big model generates specific content for a sub-account, if the specific content quality is relatively high, it can be used to divert traffic to the country / region account or main account by mentioning the specific country / region account or main account in the specific content. Or, after the main account or country / region account publishes certain content, it can be forwarded through the sub-account, so that the content published by the main account or country / region account can be more effectively reached to a certain segment of the population through these sub-accounts, etc.

[0066] In actual applications, in addition to being able to intelligently generate and publish specific content through the AI ​​big model, the AI ​​big model can also be used to generate intelligent reply content. For example, when a user comments on the content posted by an account, the AI ​​big model can be used to intelligently generate reply content. Or, after a user sends a private message to an account, the AI ​​big model can also be used to intelligently generate reply content, and so on.

[0067] The specific implementation scheme provided in the embodiments of the present application is described in detail below.

[0068] Embodiment 1

[0069] First, the first embodiment of the present application provides a method for providing social media network account operation management services, which is applied to an account operation management service system. For details, see Figure 2 , the method may include:

[0070] S201: Determine a social media network SNS account matrix system of the target subject, wherein the account matrix system includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, wherein the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-account has its own account portrait positioning in terms of specific segments of the population, industries and / or product categories.

[0071] When providing account operation services through the solution provided in the embodiment of the present application, an SNS account matrix system can first be constructed for a specific target entity. The specific target entity is the entity with account operation needs, which can be an e-commerce platform, or a merchant on the e-commerce platform, or other corporate parties, etc.

[0072] Regarding the SNS account matrix system, it can be specifically the aforementioned three-layer account matrix system, such as Figure 3 As shown, the first layer can be the main account, the middle layer can be the country / region account, and the third layer is the sub-account, which can be some accounts registered by the current subject itself, or it can also be accounts registered by other subjects and authorized to operate by the current subject. Of course, whether it is registered by the current subject or other subjects, such sub-accounts can have their own account portrait positioning, for example, for a segmented group of people in a vertical field, or a certain industry, a certain product category, etc.

[0073] Among them, since there are usually multiple SNS networks, the same subject can have multiple different main accounts corresponding to multiple different SNS networks. In addition, the same subject can also open country / region accounts in multiple different SNS networks in the same country / region. For example, assuming that there are M SNS networks and N countries / regions, a subject can correspond to M×N country / region accounts at most. Of course, in actual applications, you can also choose to open country / region accounts only in some SNS networks and some countries / regions, and so on. Regarding sub-accounts, each country / region account can have multiple different sub-accounts to achieve different refined operations for multiple different segments of the population within the same country / region.

[0074] In the specific implementation, an interface for configuring account information for the target entity can be provided to the user (who may be the operator of a certain entity, etc.). In this way, the user can prepare various accounts in advance and enter the information of various specific accounts through the interface, for example, the main account of a certain target entity, what are the country / region accounts of various countries / regions, what are the sub-accounts under the country / region account, and so on.

[0075] S202: Automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system through the artificial intelligence AI big model; wherein the content publishing strategy corresponding to the authorized sub-account is related to the account portrait positioning of the account.

[0076] After constructing the three-layer account matrix system, since there are a large number of accounts in the matrix, and different accounts may have different account portrait positioning, including corresponding to different countries / regions, different vertical fields, segmented populations, industries, categories, etc., therefore, when publishing content through specific accounts, different content needs to be generated for different accounts to meet the settings of their respective portrait positioning. Based on the above situation, the embodiment of the present application provides an implementation method for generating and publishing content for specific accounts through an AI big model.

[0077] Specifically, when generating content for the authorized sub-account through the AI ​​big model, hot spot data can be collected first, and specific content can be generated based on these hot spot data. Among them, when collecting hot spot data, it can be achieved in a variety of ways. For example, when the target subject is an e-commerce platform, the on-site hot spot data of the e-commerce platform system can be collected, and the off-site hot spot data can also be collected, and so on. Among them, for the on-site hot spot data, that is, the on-site hot spot data of the e-commerce platform, it is specifically possible to collect user hot search terms, new products, hot selling activities (such as large-scale promotions, etc.), and you can also select good performing ideas from external creative ideas, etc. For off-site hot spot data, you can collect SNS hot posts, hot selling lists in other e-commerce platforms, holiday information and other data by connecting to third-party tools and other methods.

[0078] In the process of real-time hot data capture, simply generating content based on current hot data may bring a series of problems, such as negative hot information is not suitable for posting, similar hot fatigue, and the positioning of hot spots and current subjects is inconsistent. The existence of these problems may cause users to lose interest in content, thus affecting the overall benefits of the platform.

[0079] Therefore, in practical applications, after collecting hot data from inside and outside the station, some data cleaning processing can be performed, which can be mainly divided into the following aspects:

[0080] Negative hot data information filtering: If the hot data information contains negative emotions (such as negative comments, crisis events, etc.), the hot data can be discarded, the evaluation results can be recorded and subsequent analysis can be carried out.

[0081] Hotspot fatigue detection: Check whether the hotspot data information is highly repeated with recently released content. If so, you can abandon the release of the content corresponding to the hotspot data, or consider differentiated processing of the content.

[0082] Account matching filtering: Compare the current hot data information with the account portrait positioning associated with the current subject. If the content is obviously inconsistent with the account portrait positioning (such as target audience, brand tone, etc.), the content can be abandoned.

[0083] Risk control tagging and filtering: The collected hot data can be automatically tagged for risk control to carry out risk control.

[0084] After the hot data is cleaned, specific content generation is performed. In order to improve the quality of content generation, multiple content types can be pre-defined, and detailed meanings and publishing purposes can be provided for each content type. This information can be used as prompt information for the big model, so that the big model can generate content in a more directional and targeted manner, thereby improving the quality of the specific generated content.

[0085] For example, when a cross-border e-commerce platform is the current target entity, the specific defined content types and corresponding detailed meanings may include:

[0086] Product recommendations: For hot information, we can recommend products related to the hot topic based on the needs and interests of users. For example, if the current hot topic is environmental protection, we can recommend some sustainable development products, such as eco-friendly bags, products made of renewable materials, or green cleaning products;

[0087] Event lucky draw: Based on the current hot topics, you can design a related lucky draw event to attract user participation and enhance interactivity. For example, if the recent hot topic is the release of a popular movie, you can launch peripheral products related to the movie theme as prizes;

[0088] Brand promotion: When promoting a brand, you can use hot events to enhance the brand's popularity and reputation. For example, when society pays attention to a public welfare activity, you can combine the brand's social responsibility and publish promotional content about participating in the activity to demonstrate the current subject's values ​​and sense of mission;

[0089] Rewrite popular posts: Rewrite or summarize the content of some popular posts based on current hot topics to attract users' attention and participation. For example, if a TV series has recently generated a lot of discussion, you can rewrite the popular post to "Who is your favorite character?" and encourage users to share their opinions and experiences;

[0090] Creative voting: Initiate creative voting activities around hot topics to allow users to participate in selection or voting. For example, during a popular event, you can conduct a vote on "Who do you think will win the championship?" or organize a "Best Creative Costume" vote during popular festivals such as Halloween to increase user interaction and participation;

[0091] Industry dynamics: Combine industry dynamics related to hot topics, focus on key events or trends, and provide users with timely information updates. For example, if a popular technology product is recently released, you can write a related industry analysis article to interpret the impact of the product on the market;

[0092] Knowledge sharing: Share professional knowledge around hot topics and provide valuable content to users. For example, if the current hot topic is healthy eating, you can write a guide on how to choose healthy food, or organize online lectures and invite experts to share relevant knowledge to enhance users' trust and brand image.

[0093] Of course, other content types may also be included in the specific implementation. In addition, different content types may also be defined for different types of subjects, which are not listed here one by one.

[0094] In the case where multiple content types are predefined, an AI big model for decision-making can also be provided. Through this SI big model, the collected hot data can be understood to determine the appropriate content type, as well as the appropriate country / region, target population, industry and / or commodity category, and at least one target sub-account related to the target country / region, target population, industry and / or commodity category can also be determined. In other words, for the collected hot data, the AI ​​big model can be used to understand and analyze it to determine what type of content is suitable for publishing, as well as which country / region, population, etc. are suitable for publishing, and then determine which sub-accounts are used for publishing. For example, assuming that a hot data is related to the "nail art" industry, and the hot data comes from the best-selling list of an e-commerce platform in a certain country / region, it can be determined that the hot data is suitable for publishing to people related to "nail art" in the country / region. Therefore, a sub-account related to the industry can be selected from the sub-accounts under the country / region, and so on.

[0095] After determining which sub-accounts need to be published, the corresponding content generation can be performed. Among them, since different sub-accounts have their own account image positioning, even if they are facing the same group of people or industry, different sub-accounts may have different styles, tones, content expression habits, etc. Therefore, in order to make the generated content more diverse and reflect the characteristics of specific sub-accounts, it is also possible to pre-train the corresponding AI large models for each specific sub-account (for example, it can be achieved by using a benchmark model + multiple LoRA (Low-Rank Adaptation of Large Language Models, low-rank adaptation of large language models), etc., and multiple LoRA models are used to achieve adaptation to each sub-account, etc.). In this case, since the hot data has been collected before, the content type and the sub-accounts that need to be published have been determined, the corresponding type of content can be generated by the AI ​​large model pre-trained for these target sub-accounts, and the publishing time and other information can also be determined according to the corresponding publishing time strategy. Among them, since the specific sub-accounts usually correspond to their own country / region attributes, when generating content, the language of the corresponding country / region can be used to generate it.

[0096] Specifically, in the process of generating content through the AI ​​big model, it can be carried out according to the content publishing strategy corresponding to the specific sub-account. Among them, the content publishing strategy can be used to define the content style and content matching degree that are specifically suitable for the sub-account, and the AI ​​big model can generate content according to the specific strategy. Of course, at the beginning of the project, it may be difficult to accurately know what style is suitable for each sub-account, etc. Therefore, what needs to be done is to generate as much variety of content as possible, and then in the specific publishing process, according to the feedback from the interaction between users and content, adjust the specific content publishing strategy. For example, the features that need to be adjusted and tried are as follows:

[0097] Hotspot data quality: collect and connect as many different data sources as possible, and mark the hotspot source channel and hotspot timeliness as basic features;

[0098] Content type: Generate as many content templates as possible, such as product recommendation posts, lucky draws, brand promotions, hot post rewrites, voting, etc. For each type, you can prepare multiple prompt templates and mark them with corresponding features;

[0099] Product quality: When product recommendations are required in the generated content, in order to prevent quality problems caused by a large number of products on the site, industry operators can manually select various types of high-quality product pools, such as new product pools, hot-selling pools, industry pools, etc.

[0100] The generated content can be sorted based on the manual scoring of SNS operators. Through statistical learning, the basic weights of each feature can be obtained. In the subsequent intelligent posting plan, the content quality score can be calculated and sorted according to these weights to initially form a content publishing strategy suitable for the account.

[0101] Specifically, in the process of generating content, it is also possible to add some content related to the subject in combination with the characteristics of the current target subject itself. For example, if the specific target subject is a cross-border commodity information service platform, as mentioned above, one of the content types may include a commodity recommendation category. At this time, content related to the specific recommended commodity can be added to the generated content. Specifically, after collecting hot data and determining the content for generating commodity recommendation categories, it is also possible to determine the target commodity related to the hot data from the commodity information service platform, as well as the relevant display materials of the target commodity, including commodity pictures, titles, attributes and other information. Afterwards, the relevant display materials of the target commodity can be provided to the AI ​​big model trained for the target sub-account, so that the AI ​​big model generates text content related to commodity recommendations based on the hot data, and assembles it with the display materials into the content to be published of the commodity recommendation category.

[0102] In addition, when the AI ​​big model is used to generate content for the sub-account, the generated content can also be adapted to the SNS network's content style, format, specifications, required interactive elements and / or user preferences based on the SNS network corresponding to the target sub-account. This not only includes adjusting the tone and style of the text content, but also involves image size, format, and interactive elements required by different platforms, such as voting, Q&A, etc., to ensure that the final published content can effectively attract user attention and participation on each SNS channel. For example, a certain SNS network supports the use of tags to make the published content easier for users to discover, which is equivalent to providing multiple ways to reach a larger audience group and increase interactive precipitation. Based on this situation, a set of the most popular tag libraries can be provided, and the big model can be used to find the tags that best fit the currently generated content and integrate them into the content.

[0103] Assuming that a certain SNS network requires that the content to be published must include pictures, in the process of generating content, relevant picture materials can be obtained while generating text content, and assembled into the final content to be published. As for the picture part, it can be queried through relevant picture libraries (such as product picture libraries of e-commerce platforms, etc.), or it can be directly generated by AI large models, etc.

[0104] In addition, some SNS networks may support publishing multiple different content forms. For example, a certain SNS network can support users to publish "works" and "daily life". Among them, "works" usually have clear creation purposes and forms, aiming to express the author's emotions, thoughts, values, etc., and focus on artistry and aesthetics. "Works" often require the author to have deep thinking and rich imagination, use detailed and vivid descriptions and metaphors, and focus on language, rhythm, rhythm and other skills. "Daily life" focuses more on trivial matters and ordinary events in life, records bits and pieces of life, and does not emphasize artistry and aesthetics. Daily records can be casual and impromptu, and do not necessarily have a clear creation purpose. They are more for recording real scenes and feelings in life. In addition, there will be differences in the display time. The published "works" usually exist all the time unless the homework is deliberately deleted, while the published "daily life" usually exists within a certain time length (for example, 24 hours). When the time is up, it will be hidden and only visible to the author himself. The display objects are also different. "Works" are visible to all users on the Internet, while "daily life" can usually only be viewed by "friends" who follow the account and enter the personal homepage of the account. Based on the above, when the generated content is adapted for the SNS network, the generated content can also be rewritten in various ways to generate content corresponding to various content forms, and published in different content forms. For example, content suitable for publishing in the form of works can be generated, and content suitable for publishing in the form of daily life can also be generated, and so on. Alternatively, after generating content suitable for publishing in the form of works, the current content can also be modified through the big model to conform to the style of "daily life", including shortening the length of the copy to make it more immediate and visually impactful.

[0105] It should be noted here that when the product information service system is the posting subject, it may be necessary to often add specific product information to the content. If the product information is added directly to the content in the form of a work, there may be problems such as the frequency cannot be too high. Otherwise, it may be restricted by the rules of the SNS platform. In this case, you can also choose to rewrite the "work" content into "daily" content, and then associate specific product information in the "daily" content, and so on.

[0106] During the content publishing phase, a series of steps can be followed to ensure the security and effectiveness of the content. First, anti-AI detection is performed to determine whether the generated content meets the platform's security standards. Next, risk control verification is performed to ensure that the published content does not cause legal or ethical issues, thereby reducing risks. After that, the potential performance of the content can be evaluated based on the algorithm AI score. On this basis, a detailed publishing plan can be formulated through AI to select the best publishing time to maximize the exposure and effect of the content. Finally, after manual scoring and reconfirming the quality and spreadability of the content, it can be officially released to various SNS platforms to ensure that the content reaches the target audience smoothly. This systematic publishing process can effectively enhance the value of the content and the user's interactive experience.

[0107] In addition, during the delivery phase, you can also provide direct feedback based on user behavior data on the platform (such as number of views, number of interactions, number of likes, etc.) to further guide and improve posting strategies and quality, including:

[0108] (1) Optimize strategy model based on EE (Exploration & Exploitation, exploration is to develop unknown areas, while exploitation is to use known states)

[0109] Test different content publishing strategies, including different content styles, content types, publishing timings and frequencies. At this stage, you can focus on the diversity of user behavior and try to discover those content forms or publishing times that have not been fully utilized. Based on previous user feedback and data analysis, determine the best performing content styles and content types, and reuse and optimize them extensively to maximize user interaction and engagement.

[0110] (2) Optimization of release timing and frequency

[0111] By analyzing the user's active time period, you can understand when to post to get the best interaction effect. At the same time, test different posting frequencies to ensure that you get the best time and frequency for posting without disturbing users too much.

[0112] (3) Optimize copywriting quality

[0113] Based on user feedback, we can collect similar high-quality content from the same account and continuously train the AI ​​post copy generation model for the corresponding strategy, and confirm the improvement effect through manual scoring, A / B testing, etc.

[0114] (4) Product quality optimization

[0115] When the product information service system is the posting entity, in addition to estimating product quality through on-site product model scoring, it can also directly ask users to provide feedback on their preference for products by initiating questionnaires, and directly replace products in the product pool based on voting data.

[0116] (5) Improvement of account profile

[0117] Continuously monitor and analyze user browsing, interaction and other behaviors, and combine user data feedback from the platform to continuously improve the user preferences and portraits of the corresponding population of the account, which will promote the iterative upgrade of content production quality and strategy.

[0118] In an optional implementation, in addition to generating post content through the AI ​​big model, the collaborative relationship between different accounts can also be managed to achieve mutual diversion between different accounts, etc. Specifically, in one way, the quality of the content generated by the AI ​​big model for the sub-account can be judged. If it meets the preset conditions, the country / region account and / or the main account of the country / region to which the sub-account belongs can be mentioned in the generated content to achieve interaction between the sub-account and the country / region account and / or the main account. That is to say, after the AI ​​big model generates post content for a sub-account, if the post content quality is relatively good, it can also mention the specific country / region account in its content through "@country / region account" and other methods. For example, if the content posted by a sub-account is related to a certain product, it can be reflected in the content that "If you want to know more about the product, please go to @country / region account", etc. If the user is interested in this, he can click on the country / region account link in the content to enter the homepage of the country / region account to view it, thereby achieving diversion to the country / region account, etc.

[0119] In another way, when managing the collaborative relationship between different accounts, you can also forward part of the content published by the country / region account of the country / region you belong to through the sub-account. For example, if a country / region account publishes content about platform activities, the sub-account associated with the country / region can forward the content, so that the content published by the country / region account can reach the segmented population in certain vertical fields more accurately through the sub-account.

[0120] Furthermore, it is also possible to achieve "mutual following and mutual transfer" between different sub-accounts, so that the content published by a sub-account can also be forwarded by other sub-accounts to reach more segmented groups, etc. Of course, in the process of "mutual following and mutual transfer" between sub-accounts, it is possible to avoid mutual transfer of content between sub-accounts in different industries to avoid affecting the user experience.

[0121] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of smart posting. In practical applications, in addition to smart posting, smart replies can also be implemented through the AI ​​big model. For example, after an account publishes a certain content, some users may comment on the content and may ask some questions in the comments, such as how to buy a certain product, etc. In addition, after some users view the content published by an account, they may also send private messages to the account to ask certain questions. In the case where there are many sub-accounts in the embodiment of the present application, the user's comments or private messages may also be very large. Therefore, after the account in the account matrix system receives the comment content or private message content entered by the user for the published content, the AI ​​big model can also be used to generate reply content to the comment content or private message content.

[0122] In addition, in addition to replying to the user's comments or private messages to the accounts within the system, since the accounts within the system can also follow each other, it is also possible to intelligently reply to the accounts you follow after the accounts you follow publish content. For example, a certain country / region account of a certain entity has sub-accounts A and B. These two accounts follow each other because they are related in industry fields. After sub-account A publishes a certain content, the AI ​​big model can also generate a reply to the content published by account A in the tone of sub-account B, and so on.

[0123] Furthermore, accounts within the system can also follow some popular accounts outside the system, such as influential accounts in a certain industry, etc. By following these popular accounts, the exposure of accounts within the system can be increased by commenting on the content posted by the popular accounts in a timely manner.

[0124] Alternatively, in addition to the content published by some well-known popular accounts that may have relatively high popularity, the content published by some unknown accounts may also unexpectedly become hot topics, and comments on such content can also be published in a timely manner through accounts within the system. In order to achieve this goal, a keyword and / or topic monitoring mechanism can also be set up to capture and analyze hot topics and discussion trends on the SNS platform in real time. Through the context understanding technology of the AI ​​big model, the sub-accounts related to the topic or discussion trend in the specific account matrix system are determined, and replies highly relevant to the discussion topic are generated, guiding users to the sub-account for deeper interaction and understanding. For example, there are several hot keywords related to the nail industry. You can pay attention to whether there are hot posts published under a certain keyword (for example, a surge in the number of likes, etc.). If so, you can also intervene through the AI ​​big model and publish comments on such hot posts through sub-accounts of related industries in the system, and so on.

[0125] Specifically, during the process of intelligent replying, the quality of intelligent replies can also be judged to gradually improve the quality of intelligent replies. However, during the process of intelligent posting, the quality of the content can be judged very intuitively from the user's browsing / interaction and other behaviors, but for replies, these data cannot be directly obtained. Therefore, the core solution is to classify the user's intentions through the AI ​​big model, establish different user behavior feedback standards according to different classifications, and then gradually optimize and iterate. For example, the proportion of user reply types in a cross-border commodity information service system is as follows:

[0126] Consultation / complaints: 50%

[0127] Emotional venting: 30%

[0128] Sharing: 10%

[0129] Taking consultation as an example, after responding to user consultation, you can get user feedback on the response through private messages, etc. The adoption rate is calculated based on the feedback and used to mark the AI ​​reply content, thereby promoting the continuous upgrading of AI large models and prompt strategies to improve the quality of replies.

[0130] For emotional venting, AI can be used to generate soothing responses, and the success of the response strategy can be judged by observing whether the user complains again.

[0131] It should be noted that the AI ​​big model used in the embodiments of the present application can be based on existing content generation capabilities such as existing large language models, and the data inside and outside the site, speech templates and other information can be cleaned and inputted to train a model that meets the needs of the specific main site, so that it can generate content that conforms to the characteristics of different platforms and brand tones.

[0132] In summary, through the embodiment of the present application, account operation management services can be provided for entities with cross-border account operations. Through this service, an SNS account matrix system can be constructed for specific entities. The matrix can include the main account registered by the entity in the SNS network, and can also include country / region accounts registered for multiple countries / regions. Each country / region account can also have at least one sub-account. This sub-account can be an account directly registered by the current entity in the SNS network, or it can be an account registered by other entities in the SNS network and authorized to the current entity for operation and trusteeship; wherein, this sub-account has its own account portrait positioning for specific segments of the population, industries and / or commodity categories. On the basis of constructing the above-mentioned account matrix system, the artificial intelligence AI model can also be used to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system; wherein, the content publishing strategy corresponding to the sub-account can be related to the account portrait positioning of the account, so that the content, time, etc. published by the specific sub-account are all related to the specific account portrait positioning, realizing the refined operation for each user group, so that the same sub-account can obtain the continuous attention of the corresponding population.

[0133] In an optional implementation, the AI ​​big model can also be used to perform collaborative interaction between different accounts in the account matrix system, including mentioning the country / region account and / or main account of the country / region to which the sub-account belongs in the content generated for the sub-account; or forwarding part of the content published by the country / region account of the country / region to which the sub-account belongs through the sub-account; or following each other between sub-accounts with the same or related account portrait positioning, and / or forwarding each other's published content, etc. Through such interaction between accounts, the effect of widely displaying the brand image to users can be formed, reducing the account operation cost.

[0134] In addition, intelligent replies can be achieved through the AI ​​big model, including replies to users' comments or private messages, or intelligent replies to content posted by popular accounts in the industry. Alternatively, keywords and / or topic monitoring mechanisms can be set to capture and analyze hot topics and / or discussion trend content in the SNS network in real time, and sub-accounts related to the hot topics and / or discussion trend content in the account matrix system can be determined, and content commenting on the hot topics and / or discussion trend content with the sub-account can be generated through the AI ​​big model.

[0135] Embodiment 2

[0136] In the second embodiment, corresponding to the first embodiment, a method for processing SNS account information is provided from the perspective of the user side (for example, the operator of the target entity, etc.), see Figure 4 , the method may include:

[0137] S401: receiving account configuration information submitted for a target subject through a target interface, the account configuration information including a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, the sub-account including an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-account has its own account portrait positioning in terms of specific segments of the population, industries and / or commodity categories;

[0138] S402: Constructing the SNS account matrix system of the target subject according to the account configuration information, so as to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system through the AI ​​big model; wherein, the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

[0139] Among them, the AI ​​big model can also be used for collaborative interactive processing between different accounts.

[0140] For the parts not described in detail in the second embodiment, please refer to the description of the first embodiment and other parts of this specification, which will not be repeated here.

[0141] It should be noted that the embodiments of the present application may involve the use of user data. In actual applications, user-specific personal data can be used in the scheme described herein within the scope permitted by applicable laws and regulations, subject to the requirements of applicable laws and regulations of the country where the user is located (for example, with the user's explicit consent, effective notification to the user, etc.).

[0142] Corresponding to the first embodiment, the embodiment of the present application further provides a device for providing social media network account operation management services, the device is applied to the account operation management service system, including:

[0143] An account matrix system determination unit is used to determine a social media network SNS account matrix system of a target subject, wherein the account matrix system includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, wherein the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-accounts have respective account portrait positioning in terms of specific segments of the population, industries and / or commodity categories;

[0144] The account management service unit is used to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system through the artificial intelligence AI big model; wherein the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

[0145] Wherein, when the account management service unit generates content for the sub-account through the AI ​​big model, it can be specifically used to:

[0146] Collect hotspot data;

[0147] The hot data is understood through the AI ​​big model for decision-making to determine the appropriate content type, as well as the appropriate country / region, target population, industry and / or product category, and at least one target sub-account related to the target country / region, target population, industry and / or product category is determined;

[0148] The AI ​​big model pre-trained for the target sub-account generates the corresponding type of content for the target sub-account, and determines the publishing time according to the corresponding publishing time strategy.

[0149] Specifically, the target subject includes a cross-border commodity information service platform; the content type includes a commodity recommendation category;

[0150] At this time, the device may further include:

[0151] A display material acquisition unit, used to determine a target product related to the hot data and related display materials of the target product from the product information service platform;

[0152] A display material providing unit is used to provide the relevant display materials of the target product to the AI ​​big model trained for the target sub-account, so as to generate text content related to product recommendation according to the hot data, and assemble it with the display materials into content to be published of the product recommendation category.

[0153] In addition, when the account management service unit generates content for the sub-account through the AI ​​big model, it can also be used to:

[0154] After generating the corresponding type of content for the target sub-account, the generated content is adapted to the SNS network in terms of content style, format, specifications, required interactive elements and / or user preferences according to the SNS network corresponding to the target sub-account.

[0155] In addition, it can also be used for: when performing the adaptation process, if the SNS network supports multiple different content formats, the generated content is rewritten in multiple ways to generate content corresponding to the multiple content formats, and the content is published in different content formats respectively.

[0156] Furthermore, the account management service unit may also be used to:

[0157] The content publishing strategy corresponding to the sub-account is updated according to the user's interactive feedback on the content published in the account.

[0158] Specifically, the account management service unit is also used for:

[0159] The AI ​​big model is used to carry out collaborative interactive processing between different accounts in the account matrix system.

[0160] Specifically, when different accounts in the account matrix system are collaboratively interacting with each other, it can be used to:

[0161] The quality of the content generated by the AI ​​big model for the sub-account is judged. If it meets the preset conditions, the country / region account of the country / region to which the sub-account belongs and / or the main account are mentioned in the generated content to achieve interaction between the sub-account and the country / region account and / or the main account.

[0162] Alternatively, part of the content published by the country / region account of the country / region to which it belongs is forwarded through the sub-account.

[0163] Alternatively, sub-accounts with the same or related account profiles may follow each other and / or forward each other’s content.

[0164] In addition, the device may also include:

[0165] The automatic reply unit is used to generate reply content to the comment content or private message content input by the user for the published content after the account in the account matrix system receives the comment content or private message content input by the user.

[0166] The comment content generating unit is used to follow well-known accounts outside the system in the corresponding industry or field through the sub-accounts in the account matrix system, and after the well-known accounts outside the system publish content, use the AI ​​big model to generate comment content for the published content.

[0167] Alternatively, by setting up a keyword and / or theme monitoring mechanism, hot topics and / or discussion trend content in the SNS network are captured and analyzed in real time, and sub-accounts related to the hot topics and / or discussion trend content in the account matrix system are determined, and content commenting on the hot topics and / or discussion trend content by the sub-account is generated through the AI ​​big model.

[0168] Corresponding to the second embodiment, the embodiment of the present application further provides an SNS account information processing device, which may include:

[0169] a configuration information receiving unit, configured to receive account configuration information submitted for a target subject through a target interface, wherein the account configuration information includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, wherein the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-account has its own account portrait positioning in terms of specific segments of the population, industries and / or commodity categories;

[0170] An account system construction unit is used to construct the SNS account matrix system of the target subject according to the account configuration information, so as to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system through the AI ​​big model; wherein the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

[0171] Among them, the AI ​​big model can also be used for collaborative interactive processing between different accounts.

[0172] In addition, an embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of any one of the methods in the aforementioned method embodiments are implemented.

[0173] And an electronic device, comprising:

[0174] one or more processors; and

[0175] A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of the method described in any one of the aforementioned method embodiments.

[0176] A computer program product includes a computer program / computer executable instructions, which, when executed by a processor in an electronic device, implement the steps of the method described in the aforementioned method embodiment.

[0177] in, Figure 5The architecture of the electronic device is shown as an example, which may include a processor 510, a video display adapter 511, a disk drive 512, an input / output interface 513, a network interface 514, and a memory 520. The processor 510, the video display adapter 511, the disk drive 512, the input / output interface 513, the network interface 514, and the memory 520 may be communicatively connected via a communication bus 530.

[0178] Among them, the processor 510 can be implemented by a general-purpose CPU (Central Processing Unit, processor), a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, etc., to execute relevant programs to implement the technical solution provided in this application.

[0179] The memory 520 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 520 can store an operating system 521 for controlling the operation of the electronic device 500, and a basic input and output system (BIOS) for controlling the low-level operation of the electronic device 500. In addition, a web browser 523, a data storage management system 524, and an account information processing system 525, etc. can also be stored. The above-mentioned account information processing system 525 can be an application program that specifically implements the operations of the aforementioned steps in the embodiment of the present application. In short, when the technical solution provided by the present application is implemented by software or firmware, the relevant program code is stored in the memory 520 and is called and executed by the processor 510.

[0180] The input / output interface 513 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0181] The network interface 514 is used to connect to a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0182] The bus 530 comprises a pathway for transmitting information between the various components of the device (eg, the processor 510, the video display adapter 511, the disk drive 512, the input / output interface 513, the network interface 514, and the memory 520).

[0183] It should be noted that, although the above device only shows a processor 510, a video display adapter 511, a disk drive 512, an input / output interface 513, a network interface 514, a memory 520, a bus 530, etc., in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include components necessary for implementing the solution of the present application, and does not necessarily include all the components shown in the figure.

[0184] It can be known from the description of the above implementation methods that those skilled in the art can clearly understand that the present application can be implemented by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present application can be essentially or partly contributed to the prior art in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present application or certain parts of the embodiments.

[0185] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without creative work.

[0186] The above is a detailed introduction to the method and electronic device for providing social media network account operation and management services provided by the present application. This article uses specific examples to illustrate the principles and implementation methods of the present application. The above examples are only used to help understand the method and core ideas of the present application. At the same time, for those skilled in the art, according to the ideas of the present application, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as limiting the present application.

Claims

1. A method for providing social media network account operation management services, characterized in that: Applied to an account operation management service system, the method includes: Determine a social media network SNS account matrix system of the target subject, wherein the account matrix system includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, wherein the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-accounts have respective account portrait positioning in terms of specific segments of the population, industries and / or commodity categories; The artificial intelligence AI big model is used to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system; wherein the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

2. The method according to claim 1, characterized in that: When content is generated for the sub-account through the AI ​​big model, it includes: Collect hotspot data; The hot data is understood through the AI ​​big model for decision-making to determine the appropriate content type, as well as the appropriate country / region, target population, industry and / or product category, and at least one target sub-account related to the target country / region, target population, industry and / or product category is determined; The AI ​​big model pre-trained for the target sub-account generates the corresponding type of content for the target sub-account, and determines the publishing time according to the corresponding publishing time strategy.

3. The method according to claim 2, characterized in that The target entities include cross-border commodity information service platforms; The content types include product recommendation categories; The method further comprises: Determining a target commodity related to the hot data and related display materials of the target commodity from the commodity information service platform; The relevant display materials of the target product are provided to the AI ​​big model trained for the target sub-account, so as to generate text content related to product recommendation according to the hot data, and assemble them with the display materials into content to be published of the product recommendation category.

4. The method according to claim 2, characterized in that: When the content is generated for the sub-account by using the AI ​​big model, it also includes: After generating the corresponding type of content for the target sub-account, the generated content is adapted to the SNS network in terms of content style, format, specifications, required interactive elements and / or user preferences according to the SNS network corresponding to the target sub-account.

5. The method according to claim 4, characterized in that During the adaptation process, if the SNS network supports multiple different content formats, the generated content is rewritten in multiple ways to generate content corresponding to the multiple content formats, and the content is published in different content formats respectively.

6. The method according to claim 1, characterized in that Also includes: The content publishing strategy corresponding to the sub-account is updated according to the user's interactive feedback on the content published in the account.

7. The method according to claim 1, characterized in that Also includes: The AI ​​big model is used to carry out collaborative interactive processing between different accounts in the account matrix system.

8. The method according to claim 7, characterized in that The collaborative interaction process between different accounts in the account matrix system includes: The quality of the content generated by the AI ​​big model for the sub-account is judged. If it meets the preset conditions, the country / region account of the country / region to which the sub-account belongs and / or the main account are mentioned in the generated content to achieve interaction between the sub-account and the country / region account and / or the main account.

9. The method according to claim 7, characterized in that: The collaborative interaction process between different accounts in the account matrix system includes: Part of the content published by the country / region account of the country / region to which it belongs is forwarded through the sub-account.

10. The method according to claim 7, characterized in that The collaborative interaction process between different accounts in the account matrix system includes: Sub-accounts with the same or related account profiles follow each other and / or forward each other’s content.

11. The method according to claim 1, characterized in that: Also includes: After an account in the account matrix system receives a comment or private message from a user regarding a published content, the account uses the AI ​​big model to generate a reply to the comment or private message.

12. The method according to claim 1, characterized in that Also includes: Through the sub-accounts in the account matrix system, well-known accounts outside the system in the corresponding industry or field are followed, and after the well-known accounts outside the system publish content, the AI ​​big model is used to generate comment content for the published content.

13. The method according to claim 1, characterized in that Also includes: By setting up a keyword and / or theme monitoring mechanism, hot topics and / or discussion trend contents in the SNS network are captured and analyzed in real time, and sub-accounts related to the hot topics and / or discussion trend contents in the account matrix system are determined, and content commenting on the hot topics and / or discussion trend contents by the sub-account is generated through the AI ​​big model.

14. A method for processing SNS account information, characterized in that: include: Receiving account configuration information submitted for a target subject through a target interface, the account configuration information includes a main account registered by the target subject in the SNS network, multiple country / region accounts registered for multiple different countries / regions, and at least one sub-account associated with each country / region account, the sub-account includes an account registered by the target subject in the SNS network, and / or an account registered by other subjects in the SNS network and authorized to the target subject for operation and trusteeship; the sub-accounts have respective account portrait positioning for specific segments of the population, industries and / or commodity categories; An SNS account matrix system of the target entity is constructed according to the account configuration information, so as to automatically generate and publish content according to the content publishing strategy corresponding to the account in the account matrix system through the AI ​​big model; wherein the content publishing strategy corresponding to the sub-account is related to the account portrait positioning of the account.

15. The method according to claim 14, characterized in that The AI ​​big model is also used for collaborative interactive processing between different accounts.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method described in any one of claims 1 to 15 are implemented.

17. An electronic device, characterized in that: include: one or more processors; as well as A memory associated with the one or more processors, the memory being used to store program instructions, wherein the program instructions, when read and executed by the one or more processors, execute the steps of the method described in any one of claims 1 to 15.

18. A computer program product comprising a computer program / computer executable instructions, characterized in that: When the computer program / computer executable instructions are executed by a processor in an electronic device, the steps of the method according to any one of claims 1 to 15 are implemented.

Images