Personality-based refinement for sentiment classification in microblog

doi:10.1016/j.knosys.2017.06.031

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 互联网大数据与信息安全

	Personality-based refinement for sentiment classification in microblog
	Lin, Junjie1 ; Mao, Wenji1,2 ; Zeng, Daniel D.1,2
发表期刊	KNOWLEDGE-BASED SYSTEMS
	2017-09-15
卷号	132 期号:132 页码:204-214
文章类型	Article
摘要	Microblog has become one of the most widely used social media for people to share information and express opinions. As information propagates fast in social network, understanding and analyzing public sentiment implied in user-generated content is beneficial for many fields and has been applied to applications such as social management, business and public security. Most previous work on sentiment analysis makes no distinctions of the tweets by different users and ignores the diverse word use of people. As some sentiment expressions are used by specific groups of people, the corresponding textual sentiment features are often neglected in the analysis process. On the other hand, previous psychological findings have shown that personality influences the ways people write and talk, suggesting that people with same personality traits tend to choose similar sentiment expressions. Inspired by this, in this paper we propose a method to facilitate sentiment classification in microblog based on personality traits. To this end, we first develop a rule-based method to predict users' personality traits based on the most well studied personality model, the Big Five model. In order to leverage more effective but not widely used sentiment features, we then extract those features grouped by different personality traits and construct personality-based sentiment classifiers. Moreover, we adopt an ensemble learning strategy to integrate traditional textual feature based and our personality-based sentiment classification. Experimental studies on Chinese microblog dataset show the effectiveness of our method in refining the performance of both the traditional and state-of-the-art sentiment classifiers. Our work is among the first to explicitly explore the role of user's personality in social media analytics and its application in sentiment classification. (C) 2017 Elsevier B.V. All rights reserved.
关键词	Sentiment Classification Social Media Analytics Personality Prediction Big Five Model
WOS标题词	Science & Technology ; Technology
DOI	10.1016/j.knosys.2017.06.031
关键词[WOS]	TEXT ; WEB
收录类别	SCI ; SSCI
语种	英语
项目资助者	National Natural Science Foundation of China(61671450 ; Ministry of Science and Technology of China(2016YFC1200702) ; 71621002)
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000407184900017
引用统计	被引频次：35[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/19846
专题	多模态人工智能系统全国重点实验室_互联网大数据与信息安全
作者单位	1.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Lin, Junjie,Mao, Wenji,Zeng, Daniel D.. Personality-based refinement for sentiment classification in microblog[J]. KNOWLEDGE-BASED SYSTEMS,2017,132(132):204-214.
APA	Lin, Junjie,Mao, Wenji,&Zeng, Daniel D..(2017).Personality-based refinement for sentiment classification in microblog.KNOWLEDGE-BASED SYSTEMS,132(132),204-214.
MLA	Lin, Junjie,et al."Personality-based refinement for sentiment classification in microblog".KNOWLEDGE-BASED SYSTEMS 132.132(2017):204-214.

条目包含的文件		下载所有文件
文件名称/大小	文献类型	版本类型	开放类型	使用许可
Personality-based re（965KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载