Method and system for calculating user influence in social network

Abstract

The invention relates to the field of a social network and is applied to a network system with social elements. The invention discloses a method and a system for calculating user influence in a social network, and in the method, the behaviors of users are analyzed so that a model of the behavior of influence spread among users is established and the mold is used for identifying the most influential people in the social network. The system records user access logs in real time. The method comprises the following steps that: (1) an influence behavior extracting module filters the interactive behaviors in the logs; (2) an influence spread calculating module determines the influence of the current behavior spread according to the type and the actor of the behavior and the emotion tendentiousness analysis of the relative content; (3) an influence updating module mergers the data generated through the increment; (4) a user ranking module incrementally calculates the most influential people; and (5) a service module appoints a target user range and sequences the target users according to the influence. The method and the system can dynamically reflect the change condition of the user influence according to the interactive behaviors of the users in the social network.

Description

technical field [0001] The invention relates to a method for calculating influence in a social network, more specifically, an influence calculation method based on user behavior analysis, and an influence-based personalized user ranking system. Background technique [0002] Social networking is an Internet application service designed to help people build social networks. It mainly provides functions such as writing blogs, posting photos, designing personal space, listening to music, and playing games. It virtualizes people's daily life in reality in the network environment. Behavior, to meet the needs of users to express themselves, communicate and share conveniently and quickly. Compared with traditional networks, social networks are characterized by user participation, that is, encouraging a large number of Internet users to jointly create content. Social networks have expanded the definition of content, adding a content type of interactive behavior in addition to the tr...

AI Technical Summary

Problems solved by technology

[0013] To sum up, the above two methods have their own shortcomings, or they do not distinguish the differences in the spread of influence between different users, or do not take into account the negative influence, or assume that users will completely copy the reality to the Internet

The existing influence calculation methods are relatively simple in design, ignoring the cheating factors, which often lead to unpredictable deviations in user ranking results, resulting in a decline in user satisfaction with the website

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