一种基于用户关联分析的热点话题识别算法

为了提高从社交网络文本信息中发现热点话题的准确率，提出一种基于用户关联分析的热点话题识别算法。该算法综合考虑词频变化率和用户权威度，词频变化率通过EMA和MACD等指标来计算，用户权威度通过建立用户关联图的方式来计算。使用基于HITS算法的话题热度度量计算方法，将词频变化率数据和用户权威度数据结合在一起，得到话题的热度值。实验结果表明，使用基于用户关联分析的热点话题识别算法能够提高热点话题发现准确率。

A Hot Topic Identification Algorithm Based on User Relevance Analysis

To improve the accuracy of detecting hot topic from social network text information, a hot topic identification algorithm based on user relevance analysis is raised. The algorithm considers both the frequency change rate of feature word and the authori- ty of users. The frequency change rate of feature word is elevated using EMA and MACD indicators and the authority of users is calculated by creating user relevance graph. We use a method based on HITS algorithm to calculate the hot value of topic by com- bining feature frequency change rate data with user authority data together. According to the result of the experiment, the hot top- ic identification algorithm based on user relevance analysis can raise the accuracy of hot topic identification.