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Abstract

Social network evolution is a major component of social network analysis. Due to ubiquitous real world uncertainty, traditional deterministic networks tend to yield analytical deviations. To lessen this bias, an intuitionistic fuzzy based method is used herein to analyze the inner-structure transformations in social networks. In addition, a conception observation community is introduced into the proposed method in order to reduce the computational load. The network density and centrality metrics are used to obtain the intuitionistic fuzzy metrics of the micro relationships. Then, the social network development trends are predicted by analyzing the changes in the metrics using a Markov chain model. The experimental results demonstrate that the proposed intuitionistic fuzzy method is advantageous to the general methods.

Keywords

Social network prediction intuitionistic fuzzy observation community Markov chain

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An intuitionistic fuzzy method for social network prediction problems

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