基于超网络的微博相似度及其在微博舆情主题发现中的应用

Purpose/significance] Accurate calculation of microblog similarity can improve the efficiency of microblog topic mining, and has practical significance for public opinion governance and information security. Aiming at the problem of sparse and high-dimensional microblog text, this paper proposes a super-edge similarity algorithm incorporating non-text features of microblog. [Method/process] The mechanism of microblog public opinion was analyzed, and the formation of microblog public opinion topic formation were expressed by super network model, and the algorithm of super-edge similarity was constructed by calculating the similarity of each subnet layer and the contribution of each subnet layer to the topic formation. [Result/conclusion] It was found that the similarity method proposed in this paper is helpful to improve the topic clustering effect of microblog public opinion information. Especially for micro blog with high similarity of literal expression, it has obvious subject differentiation.