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Development of Machine-Coded Event Data Techniques for the Analysis of Political Behavior

Development of Machine-Coded Event Data Techniques for the Analysis of Political Behavior
用于分析政治行为的机器编码事件数据技术的开发
批准号:
9410023
负责人:
Philip Schrodt
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing grant
财政年份:
1994
资助国家:
美国
项目状态:
已结题
起止时间:
1994-07-15 至 1996-12-31

项目摘要

项目成果

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中文摘要
翻译
9410023施罗德这个项目扩展并演示了政治事件数据自动编码软件的使用。事件数据是通过为特定类型的政治互动(会议、协议、威胁、军事交战等)编码新闻报道而生成的。这些数据随后可用于测试有关政治行为的假设。从历史上看,人类编码员创建事件数据。然而,在NSF国际关系数据开发项目的部分支持下,早期的工作表明,机器编码能够将事件数据代码分配给政治事件的有线服务报告,其可靠性至少与人类编码员实现的可靠性一样高。最初的机器编码系统是通过根据路透社中东新闻服务报道生成11年的事件数据集进行测试的。这些数据产生的统计结果与人类编码数据产生的统计结果几乎没有区别。过去两年,政治学研究人员可以使用数据集和机器编码程序;该系统在传统的微型计算机上运行。目前的项目将从三个方面扩展这项研究。首先,该项目将开发一个集成的数据采集和编码系统,对事件数据进行实时编码。这些数据将在互联网服务器上提供,供其他研究人员使用。该系统将对现有的人工编码事件数据提供重大改进,这些数据通常在事件发生数年后才可用。其次,该项目将以几种方式增强机器编码程序,这是根据该程序的研究经验所建议的。最后,该项目将使用机器编码数据来研究两个复杂的政治行为案例:以巴冲突和西非国家经济共同体在西非的国际分系统。这两个案例旨在展示机器编码的全部能力的使用,特别是重新编码文本的工具,以检测标准事件编码系统中可能遗漏的政治活动。除了开发事件数据分析技术外,这些研究还将有助于理解国际和国内政治制度之间的相互作用。
英文摘要
9410023 Schrodt This project extends and demonstrates the use of software for the automated coding of political event data. Event data are generated by coding news reports for specific types of political interactions: meetings, agreements, threats, military engagements, etc. These data can then be used to test hypotheses about political behavior. Historically, human coders created event data. Earlier work supported in part by the NSF's Data Development in International Relations project demonstrated, however, that machine coding is capable of assigning event data codes to wire service reports of political events with a reliability at least as great as that achieved by human coders. The initial machine-coding system was tested by generating an 11- year event data set based on Reuters news service reports for the Middle East. These data produced statistical results almost indistinguishable from those produced from human-coded data. The data set and the machine-coding program have been available to political science researchers for the past two years; the system runs on conventional microcomputers. The current project will extend this research in three ways. First, the project will develop an integrated data acquisition and coding system to code event data in real time. These data will be made available on an Internet server for use by other researchers. This system will provide a significant improvement over existing human-coded event data, which typically are not available until years after events have occurred. Second, the project will enhance the machine coding program in several ways that have been suggested by research experience with the program. Finally, the project will use the machine-coded data to study two cases of complex political behavior: the Israeli-Palestinian conflict and the ECOWAS international subsystem in West Africa. These two cases are designed to demonstrate the use of the full capabilities of machine coding, particula rly the facility for re- coding texts to detect political activities that may have been missed in the standard event coding systems. In addition to developing techniques for event data analysis, these studies will contribute to understanding the interactions between the international and domestic political systems.
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会议论文
Collaborative Research: Development of a Technology for Real Time, Ex Ante Forecasting of Intra and International Conflict and Cooperation
Collaborative Research: Development of a Technology for Real Time, Ex Ante Forecasting of Intra and International Conflict and Cooperation
Collaborative Research: Computational Methods for the Analysis of Political Event Data
AOC: Collaborative Research: The Dissent/Repression Nexus in the Middle East
国内基金
海外基金
Understanding structural evolution of galaxies with machine learning
  • 批准号:
  • 项目类别:
    省市级项目
  • 资助金额:
    10.0万元
  • 批准年份:
    2022
  • 负责人:
    Nicola Rosario Napolitano
  • 依托单位: