Social-Media-Based Public Policy Informatics: Sentiment and Network Analyses of US Immigration and Border Security
文献类型：期刊论文
| 作者 | Chung, Wingyan1; Zeng, Daniel2,3
|
| 刊名 | JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
 |
| 出版日期 | 2016-07-01 |
| 卷号 | 67期号:7页码:1588-1606 |
| 关键词 | public domain information knowledge organization systems network analysis |
| 英文摘要 | 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. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Information Systems ; Information Science & Library Science |
| 研究领域[WOS] | Computer Science ; Information Science & Library Science |
| 关键词[WOS] | BUSINESS INTELLIGENCE ; FRAMEWORK ; ANALYTICS ; SCIENCE ; WEB |
| 收录类别 | SCI ; SSCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000378644700005 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12036]  |
| 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 |
| 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. |
入库方式： OAI收割
来源：自动化研究所
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