EAGER: Prototype Tool for Visualizing Online Polarization

EAGER：在线极化可视化原型工具

• 批准号: 1247198
• 负责人: Jason Thatcher
• 金额: $ 26.27万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1247198&HistoricalAwards=false
• 关键词: EAGER; Prototype; Tool; Visualizing; Online

This study will use the 2012 election cycle as a testbed for examining and developing techniques to analyze the implications of the social web for national elections. The social web - broadly defined as the array of technologies that allow individuals to post their thoughts, pictures, and comments in a public forum - has profoundly changed the way in which political candidates, elected officials, and government agencies engage with potential supporters. As an ever-growing number of people join the plethora of available social networks (including Facebook, Twitter, Pinterest, Tumblr, Flickr, and Instagram), politicians across the world sought to develop increasingly sophisticated social web strategies that maximize their ability to engage directly with the public. At the same time, the social web has facilitated the ability of individuals to share ideas, form communities, and coordinate their actions and responses to political campaigns across time and space. Yet the sheer volume of data produced daily through this online civil discourse is overwhelming for researchers and, until recently, has defied our ability to collect, analyze, and comprehend in its entirety. This research will develop a prototype visualization tool that will allow researchers to explore the online discourse surrounding elections. This tool will capture social media posts related to selected races in the 2012 Congressional election, both incumbent districts and open seats. Monitoring and analyzing the conversations relative to these races, this study will seek to determine any correlation between social media strategies employed by political candidates in the United States and any increase in polarization in the online discourse. To analyze this discourse, the research will explore the extent that those participating in an online discourse move towards a group polarization with more extreme policies and platforms. Group Polarization is a subset of research on Choice Shifts, which reflect instances where individuals alter their opinions based on commonality, unique information surfacing, or other outside influences. Experimental research suggests that group polarization occurs because the individual has had interaction with a group of like-minded peers. The theory suggests that, after discussion among the group, the individuals will come to a consensus opinion together. Thus, when competing groups form and engage in discourse separately, we are more likely to witness increasingly polarizing opinions between the two groups. This study is relevant for computer scientists, who need to develop strategies for managing, archiving, and providing access to large and dynamic datasets, and is particularly important for social scientists because this online social discourse reflects the moods, values, and attitudes of citizens towards participating in offline civil society. Moreover, scholars need to study how the new social media affect the democratic process of elections. This study will provide an opportunity to explore strategies for collecting, aggregating, visualizing, and storing data culled from the social web. It will develop a prototype visualization tool that can be connected via APIs to visualize polarization as manifested through the social web and that will be made available to other researchers interested in studying conversations, sentiment, and the social web. Moreover, this tool will act as a first step in developing a deeper understanding of how to visually map sentiment, political action, and civic discourse over time and space. Additionally, the data collected through this project will provide the basis for future research that will enable a more detailed analysis of the data collected during the election and congressional session.

这项研究将使用2012年的选举周期作为检验和开发技术的试验平台，以分析社交网络对国家选举的影响。社交网络--广义上被定义为允许个人在公共论坛上发表想法、图片和评论的一系列技术--已经深刻地改变了政治候选人、民选官员和政府机构与潜在支持者互动的方式。随着越来越多的人加入过多的可用社交网络（包括Facebook、Twitter、Pinterest、Tumblr、Flickr和Instagram），世界各地的政治家都在寻求开发越来越复杂的社交网络策略，以最大限度地提高他们与公众直接接触的能力。与此同时，社交网络促进了个人分享想法、形成社区、协调行动和应对跨时空政治运动的能力。然而，通过这种在线公民话语每天产生的大量数据对研究人员来说是压倒性的，直到最近，我们才有能力收集，分析和理解。 这项研究将开发一个原型可视化工具，使研究人员能够探索围绕选举的在线话语。该工具将捕捉与2012年国会选举中选定种族有关的社交媒体帖子，包括现任选区和空缺席位。通过监测和分析与这些种族相关的对话，本研究将试图确定美国政治候选人采用的社交媒体策略与在线话语中两极分化的任何增加之间的任何相关性。为了分析这一话语，研究将探讨参与在线话语的人在何种程度上走向更极端的政策和平台的群体极化。群体极化是选择转移研究的一个子集，它反映了个体基于共性、独特信息表面化或其他外部影响而改变其观点的情况。实验研究表明，群体极化的发生是因为个体与一群志同道合的同龄人进行了互动。该理论认为，在群体讨论之后，个体会达成一致意见。因此，当相互竞争的群体分别形成和参与话语时，我们更有可能看到两个群体之间日益两极分化的观点。这项研究与计算机科学家有关，他们需要制定管理，归档和提供访问大型动态数据集的策略，对社会科学家来说尤其重要，因为这种在线社交话语反映了公民参与离线公民社会的情绪，价值观和态度。此外，学者们需要研究新的社交媒体如何影响选举的民主进程。 这项研究将提供一个机会，探索收集，聚合，可视化和存储从社交网络中挑选的数据的策略。它将开发一个原型可视化工具，可以通过API连接，以可视化通过社交网络表现出来的极化，并将提供给其他有兴趣研究对话，情感和社交网络的研究人员。此外，该工具将作为更深入地理解如何在时间和空间上直观地映射情感，政治行动和公民话语的第一步。此外，通过该项目收集的数据将为未来的研究提供基础，从而能够对选举和国会会议期间收集的数据进行更详细的分析。