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- W1570774628 abstract "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 “i M ood” that addresses the needs for sentiment and network analyses of U . S . immigration and border security. i M ood collects related messages on T witter, extracts user sentiment and emotion, and constructs networks of the T witter 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 M ay and N ovember 2013. Statistical analyses reveal significant differences in emotion and sentiment among the 3 phases. The T witter 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." @default.
- W1570774628 created "2016-06-24" @default.
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- W1570774628 date "2015-05-21" @default.
- W1570774628 modified "2023-09-27" @default.
- W1570774628 title "Social-media-based public policy informatics: Sentiment and network analyses of U.S. Immigration and border security" @default.
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- W1570774628 doi "https://doi.org/10.1002/asi.23449" @default.
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