New Words Enlightened Sentiment Analysis in Social Media

被引:0
|
作者
Cai, Chiyu [1 ,2 ]
Li, Linjing [1 ]
Zeng, Daniel [1 ,2 ,3 ]
机构
[1] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 10090, Peoples R China
[2] Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing, Peoples R China
[3] Univ Arizona, Dept Management Informat Syst, Tucson, AZ 85721 USA
来源
IEEE INTERNATIONAL CONFERENCE ON INTELLIGENCE AND SECURITY INFORMATICS: CYBERSECURITY AND BIG DATA | 2016年
关键词
lexicon based method; machine learning; sentiment analysis; social media;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Public sentiment permeated through social media is usually regarded as an important measure for hot event detecting, policy making and so forth, hence many governments and intelligence agencies have been launching various initiatives to facilitate theories, technologies and systems toward monitoring its fluctuation. Recently, massive new words are created and widely spread in social media, and they pose a great influence on sentiment analysis. Facing this situation, most previous work still just add those new words into sentiment lexicon, none of the existed researches focuses on the role and influence of new words in emotional expression. In this paper, we pay more attention to the influence of new words and propose two novel new words based sentiment analysis methods, named NWLb and NWSA, the former only with the help of lexicon and the latter further incorporates machine learning, which utilize the distinctive role of new words to improve the effectiveness of sentiment analysis in social media. Experiments on real social media dataset demonstrate the effectiveness and performance of our methods.
引用
收藏
页码:202 / 204
页数:3
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