一种基于情感倾向分析的网络团体意见领袖识别算法

意见领袖对网络舆情的产生和发展有着重要的指引作用,挖掘和识别网络社区中的意见领袖有重要的现实意义。结合聚类算法和分类算法的优势,提出一种基于话题内容分析的兴趣团体发现方法,以有效识别出兴趣团体。并通过分析用户回帖情感倾向来计算用户间链接的权重。在此基础上,提出了一种新的LeaderRank意见领袖发现算法,通过实验证明该算法能有效提高意见领袖挖掘的准确度。

Networking Groups Opinion Leader Identification Algorithms Based on Sentiment Analysis

Opinion leaders are core users in online communities,which can guide the direction of public opinion.We proposed a method to find the interest group based on topic content analysis,which combines the advantages of clustering and classification algorithms.Then we used the method of sentiment analysis to define the authority value as the weight of the link between users.On this basis,an algorithm named LeaderRank was proposed to identify the opinion leaders in BBS,and experiments indicate that LeaderRank algorithm can effectively improve the accuracy of leaders mining.