面向时间序列的微博话题演化模型研究-计算机科学.pdfVIP

Vo1. 44 No.8 第 44 卷第8 期 计算机科学 2017 年 8 月 COMPUTER SCIENCE Aug.2017 面向时间序列的微博话题演化模型研究 王振飞刘凯莉郑志蕴王飞 (郑州大学信息工程学院 郑州 450001) 摘 要 话题演化研究有助于追踪用户的喜好和话题的发展趋势，对于舆情预警具有重要意义。目前，话题演化方法 注重运用话题生成模型实现话题演化分析，忽略了话题中时间因素和背景词的存在。以传统话题生成模型 LDA 为基 础，将其扩展为微博话题生成模型 MTLDA， MTLDA模型增加了对背景词的考虑，提高了话题生成的效率，同时对 微博话题集进行时间片划分，利用 KL 距离计算相邻时间片话题距离，分析话题演化情况。以新浪微博数据为例进行 实验，结果表明，MTLDA模型通过时间片划分完成了微博话题的生成，话题演化结果与实际情况吻合。 关键词微博，话题演化，社交网络，MTLDA模型，KL 距离 中图法分类号 TP399 文献标识码 A 001 10. 11896/j. issn. 1002-137叉 2017.08.046 Research on Evolution Model of Microblog Topic ßased on Time Sequence WANG Zhen-fei LIU Kai-li ZHENG Zhi-yun WANG Fei (School of Information Engineering ,Zhengzhou University ,Zhengzhou 450001 ,China) Abstract Topic evolution research is helpful to track the user preferences and development trend of topics ,and it is of great significance for public sentiment warning. Current topic evolution methods focus on using topic generation model to achieve the topic evolution analysis , and ignore the time factors of topic and background word. Based on the tradi- tional topic generation model LDA ,this paper extended it to the micrcγblog topic generation model MTLDA. Conside- ring the background word ,MTLDA model improves the efficiency of the topic generation. Meanwhile ,the micro-blog topic set is divided into time slices ,KL divergence is used to calculate the distance between adjacent time slices , and topic evolution is analyzed. Taking Sina Micrσblog data as an example ,the experimental results show that the MTLDA model completes the generation of micrσblog topic by using the time slice ,and t