基于情感主题特征词加权的微博评论聚类算法研究  

Microblog comment clustering algorithm based on weighted sentiment topic feature words

作　　者：吴迪[1,2] 杨瑞欣 申超 WU Di;YANG Ruixin;SHEN Chao(School of Information and Electrical Engineering,Hebei University of Engineering,Handan 056038,China;Hebei Key Laboratory of Security&Protection Information Sensing and Processing,Handan 056038,China)

机构地区：[1]河北工程大学信息与电气工程学院,河北邯郸056038 [2]河北省安防信息感知与处理重点实验室,河北邯郸056038

出　　处：《现代电子技术》2020年第23期67-71,75,共6页Modern Electronics Technique

基　　金：国家自然科学基金资助项目(61802107);国家重点研发计划(2018YFF0301004);河北省高等学校科技攻关项目(ZD2018087,ZD2016017);河北省专业学位研究生教学案例建设项目(KCJSZ2018083);河北省自然科学基金青年基金项目(F2019402428)。

摘　　要：为了提高微博评论的情感分析聚类效果,提出一种基于情感主题特征词加权的微博评论聚类算法。该算法首先通过定义情感主题词袋提取情感主题词;然后利用语义相似度计算获得情感主题特征词,进一步通过定义情感主题特征词重要度和分布度对其进行加权,充分考虑情感主题特征词对主题的贡献度;最后通过LDA聚类获得加权的情感主题特征词。实验结果表明,该算法表现出较好的情感分析聚类效果,对网络舆情分析有一定的指导作用。In order to enhance clustering effect of sentiment analysis on microblog comments,a microblog comment clustering algorithm based on the weighted sentiment topic feature words is proposed in this paper.With the algorithm,the sentiment topic words are extracted by defining the sentiment topic word bag,and then the sentiment topic feature words are obtained by calculation of semantic similarity.The sentiment topic feature words are weighted by defining their importance and distribution.The contribution of sentiment topic feature words to the topic is considered fully in the algorithm.The weighted sentiment topic feature words have been obtained by latent Dirichlet allocation(LDA)clustering.The experimental results show that the algorithm has a good clustering effect of sentiment analysis,and has a certain guiding role for network public opinion analysis.

关 键 词：微博评论 聚类算法 LDA聚类 情感分析 特征词加权 主题词提取 

分 类 号：TN911.1-34[电子电信—通信与信息系统] TP391.1[电子电信—信息与通信工程]