Mining a microblog network on anti-corruption news with Social Network Analysis

摘要

Since 2012, anti-corruption has become a top priority in China and strong measures have been used to fight corruption among high-ranking “tigers” as well as low-level “flies”. In the era of microblog, the well-known microblog platforms in China, including Sina Weibo, Tengxun Weibo, 163 Weibo, have all been involved in the anti-corruption campaign. The authority makes the microblog platform as a channel to release news and get clues about corrupt officials. While the people use the microblogs not only to get news on the progress of the anti-corruption campaign, but to expose corrupt officials. In this paper, we demonstrate the mining of a microblog network involved in the news releasing of a corrupt official, Wei Pengyuan, from Sina Weibo, the largest microblog platform in China, with Social Network Analysis, in order to reveal the characteristics of information dissemination of anti-corruption news and get clues in improving such kind of information dissemination with microblogs. We dissect the network from two layers. On the first layer, we reveal the structural characteristics of the whole microblog network with four features, including density, clustering coefficient, geodesic distance, and cliques. On the second layer, we first analyze the structural characteristics of the individual microbloggs with four features, including degree, closeness, betweenness, and core & periphery, and then illustrate the powerful microbloggers with the help of revealing their identities in the real world.