Construction method for social network structure

Abstract

The invention discloses a construction method for a social network structure. The construction method comprises the following steps: (1) acquiring a weighted link matrix of an interaction behavior between users and a user attribute matrix F of the social network according to a social network graph model G=(V, L) of a social network to be constructed; (2) combining the weighted link matrix and the user attribute matrix to construct a comprehensive information matrix N; (3) minimizing ||W||0+lambda(rank)(W) according to the comprehensive information matrix N to obtain a link intensity matrix W of the social network, wherein the minimization restriction condition is that N=NW, diag(W)=0, and W is greater than or equal to 0; (4) obtaining G=(V, LW) by taking the link intensity matrix W serving as weight information of an edge set L in the social network graph model to construct the network structure of the social network. According to the method, modeling of the integrated social network structure can be realized, so that the correlation obtained between any users in the social network is real and can be reliably measured, and the calculating efficiency is high.

Description

technical field [0001] The invention relates to a method for constructing a social network structure, belonging to the technical field of software engineering. Background technique [0002] In recent years, with the rapid expansion of cyberspace, various forms of social media have emerged. Every day tens of millions of users gather in various social networks (references: D. Horowitz and S.D. Kamvar, "The anatomy of a large-scale social search engine," In Proc. of the 19th International Conference on World Wide Web, 2010, pp. 431–440.). The rapid development of social networks has enriched people's daily life and provided a variety of interactive media. As a combination of content, user interaction and Web2.0 technology, social network has become an important link to carry and maintain the relationship between people. [0003] A social network is usually represented by a graph model in the form: G=(V,L), where the node set V(|V|=n) corresponds to a set composed of n users,...

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Problems solved by technology

[0007] (2) The link strength based on statistics is not complete. This method can only record the "observed" user interaction information in the data, and cannot intelligently infer and estimate the missing or unobtained information; in other words, The link strength based on statistics cannot effectively estimate the mutual relationship between arbitrary users, and thus cannot describe the whole picture of the social network structure.

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