[1]杨立月,王移芝.微博情感分析的情感词典构造及分析方法研究[J].计算机技术与发展,2019,29(02):13-18.[doi:10.3969/j.issn.1673-629X.2019.02.003]
 YANG Liyue,WANG Yizhi.Research on Construction and Analysis of Emotion Dictionary in Emotion Analysis of Micro-blog[J].,2019,29(02):13-18.[doi:10.3969/j.issn.1673-629X.2019.02.003]
点击复制

微博情感分析的情感词典构造及分析方法研究()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
29
期数:
2019年02期
页码:
13-18
栏目:
智能、算法、系统工程
出版日期:
2019-02-10

文章信息/Info

Title:
Research on Construction and Analysis of Emotion Dictionary in Emotion Analysis of Micro-blog
文章编号:
1673-629X(2019)02-0013-06
作者:
杨立月王移芝
北京交通大学 计算机与信息技术学院,北京 100044
Author(s):
YANG Li-yueWANG Yi-zhi
School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China
关键词:
情感词典微博情感词典语气词词典语义规则情感分析
Keywords:
emotional dictionarymicro-blog sentiment dictionarymodal word dictionarysemantic rulesemotional analysis
分类号:
TP393
DOI:
10.3969/j.issn.1673-629X.2019.02.003
摘要:
为了提高微博情感分析的准确性,对微博情感分析中的语义规则和情感词典进行了研究。在传统基于情感词典的微博情感分析的基础上对情感词典中的微博情感词典的构造方法做了改进。首先构造情感词典,主要包括开源情感词典、具有时代特征的网络情感词典、根据情感词的位置特点构造的微博情感词典、具有明显情感倾向的语气情感词典。在词典构造完成的基础上结合中文语法规则,主要包括句间关系规则和句型关系规则,根据句间和句型关系算法计算微博句子的情感倾向性,将微博文本分为正向、负向和中性三个方面。为了提高微博分类的准确率,提出构建语气词词典,并且在语气词权重计算的方法上做出创新,同时对微博情感词典的构造方法做出了改进。实验结果表明,该方法能够提高微博情感分析的正确率。
Abstract:
In order to improve the accuracy of micro-blog sentiment analysis,semantic rules and sentiment dictionary in micro-blog sentiment analysis are studied. The constructing method of micro-blog sentiment dictionary in sentiment dictionary is improved on the basis of the traditional sentiment analysis based on sentiment dictionary. First of all,we construct the sentiment dictionary including the opensource sentiment dictionary,the net sentiment dictionary with the characteristics of the times,micro-blog sentiment dictionary based on position of emotional words on the basis of constructed dictionaries,and motional sentiment dictionary with obvious emotion tendency. Based on the completion of the construction of the lexicon,combined with the Chinese grammar rules,including the rule of relationship between sentences and rules of sentence patterns,the sentiment tendencies of Weibo sentences are calculated according to algorithm of relationship between sentences and sentence patterns. The micro-blog texts are divided into three categories:positive,negative and neutral section. In order to improve the classification accuracy,we propose to construct a modal dictionaries and make innovations in the modal weight calculation of the modal particles. At the same time,the construction method of the micro-blog sentiment dictionary is improved. Experiment shows that this method can improve the accuracy of the emotional analysis of micro-blog

相似文献/References:

[1]王义真,郑 啸,后 盾,等.基于SVM 的高维混合特征短文本情感分类[J].计算机技术与发展,2018,28(02):88.[doi:10.3969/j.issn.1673-629X.2018.02.020]
 WANG Yi-zhen,ZHENG Xiao,HOU Dun,et al.Short Text Sentiment Classification of High Dimensional Hybrid Feature Based on SVM[J].,2018,28(02):88.[doi:10.3969/j.issn.1673-629X.2018.02.020]
[2]林江豪,顾也力,周咏梅,等.基于表情符号的情感词典的构建研究[J].计算机技术与发展,2019,29(06):181.[doi:10. 3969 / j. issn. 1673-629X. 2019. 06. 037]
 LIN Jiang-hao,GU Ye-li,ZHOU Yong-mei,et al.Research on Building Sentiment Lexicon Based on Emoticons[J].,2019,29(02):181.[doi:10. 3969 / j. issn. 1673-629X. 2019. 06. 037]
[3]邱全磊,崔宗敏,喻 静.基于表情和语气的情感词典用于弹幕情感分析[J].计算机技术与发展,2020,30(08):178.[doi:10. 3969 / j. issn. 1673-629X. 2020. 08. 031]
 QIU Quan-lei,CUI Zong-min,YU Jing.Emotional Dictionary Based on Emoticons and Modal for Barrage Sentiment Analysis[J].,2020,30(02):178.[doi:10. 3969 / j. issn. 1673-629X. 2020. 08. 031]
[4]刘玉文,翟菊叶,朱文婕,等.基于文本语义的热点事件网络暴力分析方法[J].计算机技术与发展,2022,32(07):208.[doi:10. 3969 / j. issn. 1673-629X. 2022. 07. 036]
 LIU Yu-wen,ZHAI Ju-ye,ZHU Wen-jie,et al.A Text Semantics Based Approach for Cyber Violence Analysis on Hot Event[J].,2022,32(02):208.[doi:10. 3969 / j. issn. 1673-629X. 2022. 07. 036]
[5]黄卫东,程小香.基于微博平台的舆情参与主体情感强度研究[J].计算机技术与发展,2022,32(11):140.[doi:10. 3969 / j. issn. 1673-629X. 2022. 11. 021]
 HUANG Wei-dong,CHENG Xiao-xiang.Research on Emotional Intensity of Public Opinion Participants Based on Microblog Platform[J].,2022,32(02):140.[doi:10. 3969 / j. issn. 1673-629X. 2022. 11. 021]

更新日期/Last Update: 2019-02-10