CASISD OpenIR  > 系统分析与管理研究所
Leveraging multidimensional features for policy opinion sentiment prediction
Hou, Wenju; Li, Ying; Liu, Yijun1,2; Li, Qianqian1,2
KeywordPolicy opinion Sentiment prediction Deep learning Feature engineering
AbstractPrevious 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 Research AreaComputer Science
WOS SubjectComputer Science, Information Systems
WOS IDWOS:000848341500014
Citation statistics
Document Type期刊论文
Affiliation1.Jilin Univ, Coll Comp Sci & Technol, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun, Peoples R China
2.Chinese Acad Sci, Inst Sci & Dev, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Publ Policy & Management, Beijing, Peoples R China
Recommended Citation
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.
Files in This Item:
There are no files associated with this item.
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Hou, Wenju]'s Articles
[Li, Ying]'s Articles
[Liu, Yijun]'s Articles
Baidu academic
Similar articles in Baidu academic
[Hou, Wenju]'s Articles
[Li, Ying]'s Articles
[Liu, Yijun]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Hou, Wenju]'s Articles
[Li, Ying]'s Articles
[Liu, Yijun]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.