摘要
提出一种基于词频-极性强度值的情感词挖掘方法构建中文抑郁症情感词典。首先,对抑郁症患者评论语料进行有效分词,采用双向最大匹配和互信息方法选出候选情感词,再通过计算词频-极性强度值得到种子词集;然后,通过计算基础中文情感词典与种子词的语义相似度,得到抑郁症领域情感词表,将词表与种子词集合并,得到中文抑郁症情感词典。结果表明:本文提出的方法可准确地挖掘抑郁症专有领域情感词。
Extracting sentiment words from the online comments of depression patients provides a necessary basis for the effective analysis of depression patients’psychological tendency.How to build a domain-specific sentiment lexicon based on massive amounts of comments on the Web to analyse the sentiment tendencies of patients is a problem to solve.To solve this problem,this paper proposed a method of mining sentiment words based on word frequency-polarity intensity to construct Chinese depression sentiment lexicon.First,effective segment is done on the depression patients’comment corpus by using bi-direction matching method and mutual information to select candidate seed word,and calculating word frequency-polarity intensity(IW)to select seed word.Then,the seed word set is expanded to construct the Chinese depression sentiment lexicon by calculating the semantic similarity between the basic Chinese sentiment lexicon and the seed word to get the sentiment word of depression field,and adding the sentiment word to the seed word set to get the Chinese depression sentiment lexicon.The experimental results show that the method proposed in this paper can accurately mine the sentiment words of depression.
作者
尹畅
张顺香
朱广丽
张标
YIN Chang;ZHANG Shunxiang;ZHU Guangli;Zhang Biao(Colloge of Computer Science and Engineering, Anhui University of Science & Technology, Huainan 232001)
出处
《太原理工大学学报》
CAS
北大核心
2021年第1期105-110,共6页
Journal of Taiyuan University of Technology
基金
国家自然科学基金面上项目资助(62076006)
安徽省自然科学基金面上项目资助(1908085MF189)。
关键词
情感分析
双向最大匹配
词频-极性强度
语义相似度
抑郁症情感词典
sentiment analysis
bi-direction matching method
word frequency-polarity intensity
semantic similarity
depression sentiment lexicon
作者简介
通信作者:尹畅(1998-),硕士生,主要从事文本情感分析研究,(E-mail)906703613@qq.com。
