Analysis Method of Microblog Network User Behavior Based on mmsb

Abstract

The invention discloses a microblog network user behavior analysis method based on MMSB, which mainly includes: setting the mixed membership degree and transition probability matrix B of the established simulated microblog network, creating an MMSB simulated microblog network; according to the steps The MMSB microblog simulation network established in S1, the mixed membership degree and the transition probability matrix B are known, and the joint probability formula of the microblog forwarding percentage p(Y) between any two nodes in the entire microblog network can be obtained from the model According to the expression of microblog forwarding percentage p (Y) obtained in the step S2, adopt the mean field variable method to analyze; According to the microblog forwarding percentage p (Y) of the user actually measured by the simulated microblog network, and the described From the inequality obtained in step S3, the actual mixed membership degree and transition probability matrix B of the microblog network is obtained by using the coordinate ascending algorithm. This method is used to analyze the behavior information of microblog network users, and can obtain user information that is closer to the actual situation.

Description

technical field [0001] The invention belongs to the technical field of network applications, and in particular relates to the design of an MMSB-based microblog network user behavior analysis method. Background technique [0002] Weibo is an online social network, which provides a network communication platform for registered users, through which users can conduct a series of social activities, such as business, making friends, obtaining information, interacting with friends, etc. Weibo has developed into A very important information dissemination and communication tool has become a kind of enrichment and expansion of real social interaction. Weibo has a large number of registered users, and each user has different behaviors. The difference in user behavior is mainly reflected in each user's interests, hobbies, content of concern, frequency of posting Weibo, and frequency of forwarding Weibo. Therefore, analyzing user behavior is of great practical significance to the entire...

AI Technical Summary

Problems solved by technology

Although the MMBS user behavior analysis method takes into account the correlation between data and the multi-role of users, it cannot be directly applied to the microblog network for user behavior analysis, because the MMSB model divides the connection relationship between users into connection and The two relationships are not connected, and it does not take into account the fact that users in the microblog network forward multiple microblogs, that is, there are multiple connections between nodes

[0004] For Weibo, the existing user behavior analysis methods have certain limitations: many current user behavior analysis methods obtain data from a single object, and assume that the data in the network is independent, or independent under certain conditions. However, the current microblog user data are all related, so the results obtained by using these methods to analyze the microblog network are inaccurate; the existing user behavior analysis methods assume that the user only belongs to one community, and cannot mine users across The multi-role information of the community; the MMSB user behavior analysis method takes into account the data relevance, and can also mine the multi-role information of the user, but only divides the connection relationship of users in the network into two situations: connection and non-connection, and does not take into account microblog Connection weight between users

Therefore, the MMSB user behavior analysis method is not suitable for Weibo reposting network

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