Leveraging multidimensional features for policy opinion sentiment prediction

doi:10.1016/j.ins.2022.08.004

CORC > 科技战略咨询研究院 > 中国科学院科技战略咨询研究院 > 系统分析与管理研究所

	Leveraging multidimensional features for policy opinion sentiment prediction
	Hou, Wenju ; Li, Ying ; Liu, Yijun 2,3; Li, Qianqian 2,3
刊名	INFORMATION SCIENCES
	2022
卷号	610 页码:215
关键词	Policy opinion Sentiment prediction Deep learning Feature engineering
ISSN号	0020-0255
DOI	10.1016/j.ins.2022.08.004
文献子类	Article
英文摘要	Previous online policy opinion analyses based on social media data have focused on topic detection and sentiment classification of policy opinion after a given period following pol-icy implementation. These approaches are limited and inefficient because they provide no opportunity to change citizens' opinions once they have been formed. Furthermore, incor-porating auxiliary information to enrich semantic representations is vital and challenging due to limited texts, and a lack of both semantic information and strict syntactic structure. Therefore, we propose a novel framework to extract and integrate multidimensional fea-tures from user-related and policy-related social media information and predict policy comment polarity in the policy release phase. First, we construct four machine learning models for model-induced features to capture topic-related and opinion-related features and identify the policy-opinion nexus. In addition, we integrate basic and behavioral user features. Then, we leverage multidimensional features to construct a stacked learning model for predicting the policy opinion. Finally, we conduct experiments on 20 policy com-ment datasets to demonstrate that our prediction framework can effectively predict public opinion about a policy once it is released. Our model provides key insights into policy opin-ions in advance and can enable policymakers to engage in better policy communication before opinion formation. (c) 2022 Elsevier Inc. All rights reserved.
WOS关键词	SOCIAL MEDIA ; TWITTER ; NETWORK ; USERS
WOS研究方向	Computer Science
语种	英语
WOS记录号	WOS:000848341500014
内容类型	期刊论文
源URL	[http://ir.casisd.cn/handle/190111/12046]
专题	系统分析与管理研究所
作者单位	1.Univ Chinese Acad Sci, Sch Publ Policy & Management, Beijing, Peoples R China 2.Chinese Acad Sci, Inst Sci & Dev, Beijing, Peoples R China 3.Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun, Peoples R China
推荐引用方式 GB/T 7714	Hou, Wenju,Li, Ying,Liu, Yijun,et al. Leveraging multidimensional features for policy opinion sentiment prediction[J]. INFORMATION SCIENCES,2022,610:215.
APA	Hou, Wenju,Li, Ying,Liu, Yijun,&Li, Qianqian.(2022).Leveraging multidimensional features for policy opinion sentiment prediction.INFORMATION SCIENCES,610,215.
MLA	Hou, Wenju,et al."Leveraging multidimensional features for policy opinion sentiment prediction".INFORMATION SCIENCES 610(2022):215.