Evaluating system and method for community influence in social network

Abstract

The invention relates to an evaluating system and method for community influence in a social network. The method comprises the steps that a social network chart with social network users as nodes and user relationships as sides is built; according to the social network chart, the community structure of the social network is obtained by carrying out community division through the label propagation algorithm; according to the social network chart and matrixes which communities belong to, the parameter of the community influence is calculated, and the initial influence of each community is generated; according to the transmission probability model of the influence, an influence transmission probability matrix is generated; according to the influence transmission probability matrix and the community influence iterative computation model, the community influence is iterated and upgraded until the iteration end condition is met, the influence value of each community is obtained, and the sequence of the community influence, namely, the influence estimation result of each community in the social network is obtained after normalization. The system and method can effectively analyze the distribution of the community influence in the social network and can be used for high-influence community mining, thereby being capable of being applied to the fields of network marketing and the like.

Description

technical field [0001] The invention relates to the technical field of social networks, in particular to a system and method for evaluating community influence in social networks. Background technique [0002] Social influence refers to a phenomenon in which users, organizations, or communities have social relationships with other users, organizations, or communities, and their own behavior changes with changes in other users, organizations, or communities. Social influence is a common phenomenon in social networks. In social networks, a variety of factors may have an impact on influence. By analyzing the influence of nodes, communities and other individuals in the social network, we can discover the core nodes and core communities with important influence in the social network, which can be used for enterprise commercial marketing, targeted advertising, speech channel recommendation, public opinion monitoring, etc. Many fields. [0003] At present, the research on social...

AI Technical Summary

Problems solved by technology

[0005] In summary, there have been relatively complete technologies and methods for the influence analysis of individual users in social networks, but there are relatively few methods for community-level influence analysis in social networks, and there is a lack of analysis of communities in social networks. Comprehensive analysis and evaluation of influence, in the face of large-scale social network scenarios, existing methods are difficult to meet the requirements in terms of analysis effect and efficiency

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