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A topic enhanced approach to detecting multiple standpoints in web texts

文献类型：期刊论文

作者Lin, Junjie1,2; Kong, Qingchao1,2; Mao, Wenji1,2; Wang, Lei1,2
刊名INFORMATION SCIENCES
出版日期2019-10-01
卷号501页码:483-494
关键词Multiple standpoint detection Topic model Topic enhanced approach Adaptive parameter determination
ISSN号0020-0255
DOI10.1016/j.ins.2019.05.068
通讯作者Kong, Qingchao(qingchao.kong@ia.ac.cn)
英文摘要Internet has become the most popular platform for people to exchange opinions and express stances. The stances implied in web texts indicate people's fundamental beliefs and viewpoints. Understanding the stances people take is beneficial and critical for many security and business related applications, such as policy design, emergency response and marketing management. Most previous work on stance detection focuses on identifying the supportive or unsupportive attitudes towards a specific target. However, another important type of stance detection, i.e. multiple standpoint detection, has been largely ignored. Multiple standpoint detection aims to identify the distinct standpoints people hold among multiple parties, which reflects people's intrinsic values and judgments. When expressing standpoints, people tend to discuss diverse topics, and the word usage in the topics of different standpoints often varies a lot. As topics can provide latent information for identifying various standpoints, in this paper, we propose a topic-based approach to detecting multiple standpoints in Web texts, by enhancing generative classification model as well as feature representation of texts. In addition, we develop an adaptive process to determine parameter values in our approach automatically. Experimental studies on several real-world datasets verify the effectiveness of our proposed approach in detecting multiple standpoints. (C) 2019 Elsevier Inc. All rights reserved.
资助项目National Key R&D Program of China[2016QY02D0305] ; National Natural Science Foundation of China[71702181] ; National Natural Science Foundation of China[11832001] ; National Natural Science Foundation of China[71621002] ; National Science and Technology Major Project[2018ZX10201001] ; Early Career Development Award of SKLMCCS[20180208]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000480663900029
出版者ELSEVIER SCIENCE INC
资助机构National Key R&D Program of China ; National Natural Science Foundation of China ; National Science and Technology Major Project ; Early Career Development Award of SKLMCCS
源URL[http://ir.ia.ac.cn/handle/173211/26085]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_互联网大数据与安全信息学研究中心
通讯作者Kong, Qingchao
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
推荐引用方式
GB/T 7714		 Lin, Junjie,Kong, Qingchao,Mao, Wenji,et al. A topic enhanced approach to detecting multiple standpoints in web texts[J]. INFORMATION SCIENCES,2019,501:483-494.
APA Lin, Junjie,Kong, Qingchao,Mao, Wenji,&Wang, Lei.(2019).A topic enhanced approach to detecting multiple standpoints in web texts.INFORMATION SCIENCES,501,483-494.
MLA Lin, Junjie,et al."A topic enhanced approach to detecting multiple standpoints in web texts".INFORMATION SCIENCES 501(2019):483-494.

入库方式： OAI收割

来源：自动化研究所

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