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Collaborative Research: Mass Media and Representative Democracy

合作研究：大众传媒与代议制民主

基本信息

批准号：
1728558
负责人：
Christopher Wlezien
金额：
$ 8.82万
依托单位：
University of Texas at Austin
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-01 至 2021-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1728558&HistoricalAwards=false
关键词：
Collaborative Research Mass Media Representative

项目摘要

General AbstractThis project examines the role of mass media in the functioning of representative democratic government. It focuses on the frequency, accuracy, and clarity of policy cues in media content. It also explores how the public uses these cues to inform their preferences for policy in the US. The investigators begin with three important propositions. First, a responsive democratic public requires only basic levels of knowledge about policy and policy change. Second,the necessary information is (in some domains) readily available in media content. Third, citizens pick up on these cues and adjust their policy preferences accordingly. This project tests these propositions, leveraging differences in media coverage across policy areas drawing upon multiple news outlets in different regions of the country to understand variation in the opinion-policy link. The investigators hypothesize that there are areas where media coverage provides a reasonably accurate view of policy, and others in which media content is lacking. The accuracy of public perceptions of, and preferences for, policy should benefit or suffer accordingly. This project provides a unique, "big" data-driven investigation into how (and when, and why) representative democracy works. Technical AbstractThe centerpiece of this project is an automated content-analytic dataset comprised millions of news stories and television news transcripts on US public policy, across a range of spending areas, over the past 35 years. News content is drawn from full-text databases (primarily Lexis-Nexis) and analyzed using both dictionary and machine-learning approaches. The reliability and validity of the method is tested through human coding. These content-analytic data are examined alongside existing budgetary time series and opinion polling. Analyses offer the first large-scale exploration into the kinds of policy information that do, and do not, appear in media coverage. This will allow the team to assess how the policy preferences of individuals might change depending on the policy-relevant media content they consume. As part of the assessment of this influence, the team will provide a direct comparison of media coverage of policy and actual policy across eight policy areas. Results provide a new and unique view into the role that media play in representative democracy, particularly in public responsiveness to policy, across issue areas and over time.

一般摘要本项目研究大众媒体在代议制民主政府运作中的作用。它侧重于媒体内容中政策线索的频率、准确性和清晰度。它还探讨了公众如何利用这些线索来了解他们对美国政策的偏好。调查人员从三个重要命题开始。首先，积极响应的民主公众只需要有关政策和政策变化的基本知识。其次，必要的信息（在某些领域）可以在媒体内容中轻松获得。第三，公民注意到这些线索并相应地调整他们的政策偏好。该项目测试了这些主张，利用不同政策领域媒体报道的差异，利用该国不同地区的多个新闻媒体来了解舆论与政策联系的变化。调查人员假设，在某些领域，媒体报道提供了相当准确的政策观点，而在其他领域，则缺乏媒体内容。公众对政策的看法和偏好的准确性应该相应地受益或受损。该项目对代议制民主如何（以及何时以及为何）运作提供了独特的、“大”数据驱动的调查。技术摘要该项目的核心是一个自动内容分析数据集，包含过去 35 年中涉及美国公共政策的数百万条新闻报道和电视新闻记录，涉及一系列支出领域。新闻内容取自全文数据库（主要是 Lexis-Nexis），并使用字典和机器学习方法进行分析。通过人工编码测试该方法的可靠性和有效性。这些内容分析数据与现有预算时间序列和民意调查一起进行审查。分析首次对媒体报道中出现和未出现的政策信息进行了大规模探索。这将使团队能够评估个人的政策偏好可能如何根据他们消费的政策相关媒体内容而变化。作为评估这种影响的一部分，该团队将直接比较媒体对八个政策领域的政策报道和实际政策。研究结果为媒体在代议制民主中所发挥的作用提供了一种新的、独特的视角，特别是在公众对跨问题领域和长期政策的反应方面。