A social media creator management system based on multi-source behavior data analysis

Abstract

The present application relates to the technical field of Internet, in particular to a kind of intelligent screening and management system of internet-based talent resource.The system solves the problems of existing technology, such as scattered talent resource, low screening efficiency, limited analysis means, and inflexible permission management.The system includes: multi-platform talent data collection and standardized processing function, providing multi-dimensional screening mechanism of platform, price, fan quantity, etc.; supplier performance analysis and evaluation system, providing data-driven decision support through performance trend, supplier portrait and ranking modules; role-based user permission management method, realizing flexible configuration of system permissions; adaptive responsive design, ensuring good user experience on PC and mobile terminals.The present application improves the efficiency and accuracy of talent resource management, provides comprehensive data support for enterprises, and is suitable for talent resource management in fields such as advertising marketing, content creation and e-commerce cooperation.

Description

Technical Field

[0001] This invention relates to the field of Internet technology, and in particular to an intelligent screening, analysis and management system and method for internet-based talent resources. Background Technology

[0002] With the rapid development of short video and live streaming platforms, Key Opinion Leaders (KOLs) are playing an increasingly important role in brand marketing and content dissemination as an emerging media medium. Currently, mainstream short video platforms include Douyin, Xiaohongshu, Kuaishou, and Bilibili, each with a large number of KOLs from different fields and with different styles.

[0003] However, existing influencer resource management faces the following problems: First, influencer resources are scattered across different platforms, and the data is not unified; second, influencer selection lacks systematic and intelligent methods and often relies on human experience; third, there is a lack of standardized analytical tools for influencer evaluation and supplier management; and fourth, user permission management is not flexible enough and is difficult to adapt to complex corporate organizational structures.

[0004] Traditional talent management typically relies on spreadsheets, communication software, or simple database systems, lacking multi-dimensional screening, intelligent analysis, and collaborative management capabilities, thus failing to meet enterprises' needs for efficient and accurate talent management. Furthermore, existing technologies lack the ability to systematically analyze and evaluate supplier performance, making it difficult to provide comprehensive support for enterprise decision-making.

[0005] Therefore, there is an urgent need for a system that can integrate influencer resources from multiple platforms and provide intelligent screening, analysis, and management functions to improve the efficiency and decision-making quality of enterprises in the field of influencer marketing. Summary of the Invention

[0006] The purpose of this invention is to provide a social media creator management system based on multi-source behavioral data analysis, which aims to solve the problems of scattered influencer resources, low screening efficiency, limited analysis methods, and inflexible permission management in the existing technology, and to achieve efficient screening, accurate analysis and collaborative management of online influencer resources.

[0007] The technical solution of the present invention is as follows.

[0008] A method for intelligent screening and management of internet-based influencer resources includes the following steps: Collect influencer data from multiple platforms, including personal information, follower data, pricing data, and interaction data; build an influencer resource database and standardize and categorize the influencer data for storage. It offers a multi-dimensional filtering mechanism, including a combination of filtering based on platform, price, fan base, region, and influencer type. Generate a list of qualified influencers based on the selection criteria; It provides a car selection function based on expert resources, and supports batch operation and export of multiple experts; AI-based intelligent matching and recommendation of influencer resources; The filtered results are displayed adaptively on multiple terminal devices.

[0009] The multi-platform influencer data includes influencer information from platforms such as Douyin, Xiaohongshu, Kuaishou, and Bilibili, and the personal information includes nickname, gender, region, platform ID, etc.

[0010] The multi-dimensional filtering mechanism includes: platform filtering: filtering based on the platform to which the influencer belongs; price filtering: setting predefined price ranges and custom price ranges, filtering based on the influencer's collaboration price; fan filtering: setting predefined fan number ranges and custom fan number ranges, filtering based on the number of influencers' fans; influencer type filtering: filtering based on influencer type tags; and combined filtering: applying multiple filtering conditions simultaneously.

[0011] The AI-powered influencer resource intelligent matching and recommendation function is based on multi-dimensional data such as user's historical selection records, influencer's historical collaboration performance, and influencer-brand relevance analysis. It uses machine learning algorithms to recommend the most suitable influencer resources for users.

[0012] A supplier performance analysis and evaluation system, comprising: The supplier basic data collection module is used to collect data such as basic supplier information, cooperation history, influencer resources, and customer service. The performance trend analysis module is used to analyze the historical trends of indicators such as supplier cooperation amount, number of influencers, and number of customers served. The supplier profiling and analysis module is used to visualize supplier performance across multiple dimensions, including cooperation frequency, quality, timeliness, cost, and service quality, through radar charts and other visual methods. The supplier ranking module is used to rank suppliers based on metrics such as cooperation amount, order quantity, and number of customer services. The adaptive responsive display module is used to optimize the display of analysis results on different terminal devices.

[0013] The performance trend analysis module uses time series analysis to support the display of supplier performance change curves by different time dimensions such as monthly, quarterly, and annual.

[0014] The supplier profiling and analysis module constructs a supplier capability characteristic model by scoring the supplier's historical cooperation data from multiple dimensions, and intuitively displays the supplier's strengths and weaknesses in the form of a radar chart.

[0015] It also includes a data export module, which supports exporting analysis results in multiple formats for use in external reports or further analysis.

[0016] A role-based user access control method includes the following steps: Construct a system function permission model to divide system functions into different permission levels; Create roles and set the permission sets corresponding to those roles; Assign roles to system users; a user can be associated with one or more roles. When a user requests system resources, authentication and access control are performed based on the permission set of the user's role. It supports dynamic adjustment of permissions. When a role's permissions are modified, the permissions of all users associated with that role are updated synchronously.

[0017] The system function permission model includes three levels of permission control: menu permissions, operation permissions, and data permissions.

[0018] The beneficial effects of this invention are: (1) It has achieved unified management of influencer resources across multiple platforms, solving the problem of dispersed influencer resources; (2) It provides a multi-dimensional and intelligent talent selection mechanism, which improves the efficiency and accuracy of the selection process; (3) The supplier performance analysis and evaluation system provides data-driven decision support for enterprises; (4) Role-based user access management improves system security and management flexibility; (5) Adaptive responsive design ensures a good user experience on various terminal devices. Attached Figure Description

[0019] Figure 1 is an overall framework diagram of an embodiment of the present invention.

[0020] Figure 2 is a flowchart of the intelligent screening and management method for talent resources in an embodiment of the present invention.

[0021] Figure 3 is a schematic diagram of the multi-dimensional screening mechanism in an embodiment of the present invention.

[0022] Figure 4 is a diagram of the module composition of the supplier performance analysis and evaluation system in an embodiment of the present invention.

[0023] Figure 5 is an example of a radar chart for supplier profiling analysis in an embodiment of the present invention.

[0024] Figure 6 is a flowchart of the role-based user permission management method in an embodiment of the present invention.

[0025] Figure 7 is an example of the interface of the system on the PC in an embodiment of the present invention.

[0026] Figure 8 is an example of the interface of the system on a mobile device in an embodiment of the present invention.

Claims

1. A method for intelligent screening and management of internet-based influencer resources, characterized in that, Includes the following steps: • Collect influencer data from multiple platforms, including personal information, follower data, pricing data, and interaction data; • Build a database of influencer resources, and standardize and classify the influencer data for storage; • Offers a multi-dimensional filtering mechanism, including a combination of filtering based on platform, price, fan base, region, and influencer type; • Generate a list of influencers who meet the selection criteria; • Provides a car selection function based on expert resources, supporting batch operation and export of multiple experts; • Intelligent matching and recommendation of influencer resources based on artificial intelligence; • Adaptively display the filtered results on multiple terminal devices.

2. The intelligent screening and management method for talent resources according to claim 1, characterized in that, The multi-platform influencer data includes influencer information from platforms such as Douyin, Xiaohongshu, Kuaishou, and Bilibili. The personal information includes nickname, gender, region, platform ID, etc.

3. The intelligent screening and management method for talent resources according to claim 1, characterized in that, The multi-dimensional screening mechanism includes: • Platform filtering: Categorize and filter influencers based on the platforms they belong to; • Price filtering: Set predefined price ranges and custom price ranges to filter based on influencer collaboration prices; • Fan filtering: Set a predefined fan number range and a custom fan number range to filter based on the number of fans an influencer has; • Influencer Type Filtering: Filter by influencer type tags; • Combined filtering: Apply multiple filtering criteria simultaneously.

4. The intelligent screening and management method for talent resources according to claim 1, characterized in that, The AI-powered influencer resource intelligent matching and recommendation function is based on multi-dimensional data such as user's historical selection records, influencer's historical collaboration performance, and influencer-brand relevance analysis. It uses machine learning algorithms to recommend the most suitable influencer resources for users.

5. A supplier performance analysis and evaluation system, characterized in that, include: • Supplier basic data collection module, used to collect data such as supplier basic information, cooperation history, influencer resources, and customer service; • Performance trend analysis module, used to analyze the historical trends of indicators such as supplier cooperation amount, number of influencers, and number of customers served; • Supplier profiling and analysis module, used to visualize supplier performance across multiple dimensions such as cooperation frequency, quality, timeliness, cost, and service quality through radar charts and other visual methods; • Supplier ranking module, used to rank suppliers according to indicators such as cooperation amount, order quantity, customer service quantity; • Adaptive responsive display module, used to optimize the display of analysis results on different terminal devices.

6. The supplier performance analysis and evaluation system according to claim 5, characterized in that, The performance trend analysis module uses time series analysis to support the display of supplier performance change curves by different time dimensions such as monthly, quarterly, and annual.

7. The supplier performance analysis and evaluation system according to claim 5, characterized in that, The supplier profiling and analysis module constructs a supplier capability characteristic model by scoring the supplier's historical cooperation data from multiple dimensions, and intuitively displays the supplier's strengths and weaknesses in the form of a radar chart.

8. The supplier performance analysis and evaluation system according to claim 5, characterized in that, It also includes a data export module, which supports exporting analysis results in multiple formats for use in external reports or further analysis.

9. A role-based user access control method, characterized in that, Includes the following steps: • Construct a system function permission model to divide system functions into different permission levels; • Create roles and set the permission sets corresponding to those roles; • Assign roles to system users; a user can be associated with one or more roles. • When a user requests system resources, authentication and access control are performed based on the permission set of the user's role; • Supports dynamic adjustment of permissions. When a role's permissions are modified, the permissions of all users associated with that role are updated synchronously.

10. The role-based user permission management method according to claim 9, characterized in that, The system's functional permission model includes three levels of permission control: menu permissions, operation permissions, and data permissions.

11. A computer program product of the method or system according to any one of claims 1-10, characterized in that, It includes a computer-readable storage medium on which a computer program is stored, the computer program being executed by a processor to implement the steps of the method or system as described in any one of claims 1-10.

12. An electronic device for implementing the method or system of any one of claims 1-10, comprising a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method or system of any one of claims 1-10.

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