情报杂志Issue(11)：183-187,5.DOI:10.3969/j.issn.1002-1965.2015.11.033
基于Clauset和PageRank的社交网络族群兴趣发现研究
Study on Groups Interest in Social Network Service Based on Clauset and PageRank
王仁武 1袁毅 1翟伯荫1
作者信息
- 1. 华东师范大学商学院信息学系 上海 200241
- 折叠
摘要
Abstract
The traditional topic detection method can realize the automatic identification of the new topic in the news media information flow, which is mainly aimed at the long text information and is not suitable for data sparse microblogs. Therefore, this paper proposes a user-language-based topic thesaurus to build the keywords co-occurrence diagrams of microblog topic identification. On this basis, the Clauset algorithm and PageRank algorithm are used to carry out the modular clustering. Concerning the Clauset, different interest groups are identified from the perspective of the content, and their community structure is relatively flat;As for the PageRank, different interest clusters are found from the perspective of people, the opinion leaders of the clusters are the authority figures of social reality, and their community structure show a more significant level of resistance.关键词
词共现图/族群兴趣/Clauset PageRankKey words
word co-occurrence diagram/group interest/Clauset PageRank分类
社会科学引用本文复制引用
王仁武,袁毅,翟伯荫..基于Clauset和PageRank的社交网络族群兴趣发现研究[J].情报杂志,2015,(11):183-187,5.
