RIDIR: Modernizing Political Event Data for Big Data Social Science Research

RIDIR：大数据社会科学研究的政治事件数据现代化

• 批准号: 1539302
• 负责人: Patrick Brandt
• 金额: $ 149.74万
• 依托单位: University of Texas at Dallas
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1539302&HistoricalAwards=false
• 关键词: RIDIR; Modernizing; Political; Event; Data

The project creates a general research platform to study civil protests, international conflict, and civil unrest using texts from Spanish, Arabic, and French, in addition to English. This expands the development of programs, data and services available for coding regional conflict and cooperation methods beyond the current English-only approaches to enable data-rich research that will advance new approaches to core questions in the social, behavioral, and economic sciences. The project includes an openly available website that allows for the extraction and reporting of conflict events across the globe as well as the identification of their causes and diffusion. The project's data and methods help make data-driven decisions about foreign policy, civil war prevention, human rights policies, and the effects of other factors such as environmental or economic policies on these phenomena. The project creates large-scale civil and inter-state conflict measures, covering multiple news sources and with a common methodology in an open framework. Using multiple news data sources reduces the biases inherent in coding from a single or small set of news sources, a common approach in the past. The project aims to facilitate the coding of more, and better, data across languages, space and time, thus facilitating the study of substantive questions in traditionally underrepresented countries, peoples, and topics. Further, usability considerations generate new software for the user interface for dealing with big data like that proposed in this research, as well as server-side optimizations that scale large datasets across a diverse set of users. The scale of the event data, covering multiple years and large-scale news databases, will generate many millions of observations over space and time. Research tools, data extraction, and other user interfaces are developed to allow the relevant research communities to have access to, queries of, and citation streams for these data. Finally, machine-coded data from news reports is validated across news sources, languages, actors, ontologies, and against human-coded gold standard records. The research and data serve as inputs for understanding the effects of climate on spatio-temporally referenced civil conflict events in Latin American, Africa, the Middle East, and worldwide.

该项目还创建了一个一般研究平台，除了英语外，还使用西班牙语，阿拉伯语和法语的文本研究民事抗议，国际冲突和内乱。 这扩大了用于编码区域冲突和合作方法的计划，数据和服务的开发，而不是当前仅使用英语的方法，以实现数据丰富的研究，这些研究将推动新的方法在社会，行为和经济科学领域提出核心问题。该项目包括一个公开可用的网站，该网站允许提取和报告全球冲突事件，并确定其原因和扩散。该项目的数据和方法有助于制定有关外交政策，内战预防，人权政策以及其他因素（例如环境或经济政策）对这些现象的影响的决定。 该项目创建了大规模的民事和州间冲突措施，涵盖了多个新闻来源，并在开放框架中采用了共同的方法。 使用多个新闻数据源可减少从单个或少量新闻来源编码固有的偏见，这是过去一种常见的方法。该项目旨在促进跨语言，时空的更多，更好的数据编码，从而促进在传统上代表性不足的国家，人民和主题中研究实质性问题的研究。此外，可用性注意事项为用户界面生成了新软件，用于处理本研究中提出的大数据，以及服务器端的优化，以扩展大型数据集跨各种用户。 事件数据的规模涵盖了多年和大规模的新闻数据库，将在时间和时间上产生数百万个观察结果。 开发了研究工具，数据提取和其他用户界面，以允许相关的研究社区可以访问，查询和引用这些数据的问题。 最后，在新闻来源，语言，参与者，本体论以及针对人工编码的黄金标准记录之间验证了来自新闻报告的机器编码数据。该研究和数据是理解气候对拉丁美洲，非洲，中东和全世界时空引用的民间冲突事件的影响的投入。