Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security

doi:10.1002/asi.23449

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

	Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security
	Chung, Wingyan 1; Zeng, Daniel2,3
发表期刊	JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
	2016-07-01
卷号	67 期号:7 页码:1588-1606
文章类型	Article
摘要	Social media provide opportunities for policy makers to gauge pubic opinion. However, the large volumes and variety of expressions on social media have challenged traditional policy analysis and public sentiment assessment. In this article, we describe a framework for social-media-based public policy informatics and a system called iMood that addresses the needs for sentiment and network analyses of U.S. immigration and border security. iMood collects related messages on Twitter, extracts user sentiment and emotion, and constructs networks of the Twitter users, helping policy makers to identify opinion leaders, influential users, and community activists. We evaluated the sentiment, emotion, and network characteristics found in 909,035 tweets posted by over 300,000 users during three phases between May and November 2013. Statistical analyses reveal significant differences in emotion and sentiment among the 3 phases. The Twitter networks of the 3 phases also had significantly different relationship counts, network densities, and total influence scores from those of other phases. This research should contribute to developing a new framework and a new system for social-media-based public policy informatics, providing new empirical findings and data sets of sentiment and network analyses of U.S. immigration and border security, and demonstrating a general applicability to different domains.
关键词	Public Domain Information Knowledge Organization Systems Network Analysis
WOS标题词	Science & Technology ; Technology
DOI	10.1002/asi.23449
关键词[WOS]	BUSINESS INTELLIGENCE ; FRAMEWORK ; ANALYTICS ; SCIENCE ; WEB
收录类别	SCI ; SSCI
语种	英语
项目资助者	U.S. Department of Homeland Security ; U.S. National Science Foundation(DUE-1141209) ; National Center for Border Security and Immigration at the University of Arizona ; Center for Business Intelligence and Analytics at Stetson University
WOS研究方向	Computer Science ; Information Science & Library Science
WOS类目	Computer Science, Information Systems ; Information Science & Library Science
WOS记录号	WOS:000378644700005
引用统计	被引频次：28[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/173211/12036
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.Univ Cent Florida, Inst Simulat & Training, 3100 Technol Pkwy, Orlando, FL 32826 USA 2.Univ Arizona, Dept Management Informat Syst, Eller Coll Management, 1130 East Helen St, Tucson, AZ 85721 USA 3.Chinese Acad Sci, State Key Lab Management & Control Complex Syst, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Chung, Wingyan,Zeng, Daniel. Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security[J]. JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY,2016,67(7):1588-1606.
APA	Chung, Wingyan,&Zeng, Daniel.(2016).Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security.JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY,67(7),1588-1606.
MLA	Chung, Wingyan,et al."Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security".JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY 67.7(2016):1588-1606.