Doctoral Dissertation Research: Sectarianism Without Borders: Big Data and Experimental Analyses of Transnational Sunni-Shia Conflict

博士论文研究:宗派主义无国界:逊尼派与什叶派跨国冲突的大数据与实验分析

基本信息

  • 批准号:
    1647450
  • 负责人:
  • 金额:
    $ 2.36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-04-15 至 2019-03-31
  • 项目状态:
    已结题

项目摘要

General AbstractSectarian violence in the Middle East and Arab World have increased to their highest levels since the Iran-Iraq war in the 1980s. Violent conflict between Sunni and Shia sects can be found in a number of countries throughout the Middle East. While a large volume of qualitative literature address such this topic, we lack rigorous quantitative studies into the factors that lead to such violence, along with factors that serve to escalate or mitigate sectarian tensions in the region. Relatedly, scholars know little about the effects of heightened Sunni-Shia hostility on citizens' political attitudes and behaviors in the affected regions. Drawing on research in political science and social psychology, the PI will conduct an empirical examination of the causes and consequences of sectarian animosity in the Arab World, paying particular attention to those factors that may lead to reductions in the levels of violence. To gain a deeper understanding of the causes of sectarian conflict, the investigator utilizes a unique data set comprised of Twitter and Google Trends data, real-time event data, public opinion polls, as well as results from a lab experiment. Substantively, this project will offer empirical insights into the dynamics of a precarious source of conflict and violent extremism, with key ramifications both for regional stability and global security.Technical AbstractTo examine the causes of sectarian tensions, the PI will use Twitter and event data to explore how exogenous violent events lead to the escalation in sectarian hostility, and the role political and religious elites play in this process. The PI proposes to administer a series of household survey, timed to coincide with Shia religious holidays to assess the causal effect of elevated sectarian tensions on attitudes toward democracy, authoritarianism, and extremism. Additionally, the PI will utilize an experimental design to test the degree to which emphasizing common threats and experiences of victimization might serve to reduce outgroup prejudice among Sunni and Shia Muslims in two ways. First, by conducting the experiment on a sample comprised of students, and secondly, through the use of a Twitter experiment. By adopting innovative methodological approaches that build upon and help reconcile existing theories of intergroup relations, this project makes important contributions to both political science and social psychology. Furthermore, by helping to identify causes and consequence of sectarian hostility, and by providing empirically validated approaches to combat such tensions, this work is poised to provide valuable insights to policy makers and academics alike.
自1980年代伊朗 - 伊拉克战争以来,中东和阿拉伯世界的一般摘要暴力已上升到最高水平。 逊尼派和什叶派之间的暴力冲突在整个中东的许多国家都可以找到。尽管大量的定性文献解决了这样的主题,但我们缺乏对导致这种暴力的因素的严格定量研究,以及用于升级或减轻该地区宗派紧张局势的因素。 相关的是,学者们对逊尼派 - 什叶派对公民对受影响地区的政治态度和行为的影响的影响一无所知。 PI利用政治学和社会心理学的研究,将对阿拉伯世界中宗派仇恨的原因和后果进行经验检查,特别关注可能导致暴力水平降低的因素。 为了更深入地了解宗派冲突的原因,研究人员使用了一个独特的数据集,该数据集由Twitter和Google趋势数据,实时事件数据,公众意见民意调查以及实验实验的结果组成。 Substantively, this project will offer empirical insights into the dynamics of a precarious source of conflict and violent extremism, with key ramifications both for regional stability and global security.Technical AbstractTo examine the causes of sectarian tensions, the PI will use Twitter and event data to explore how exogenous violent events lead to the escalation in sectarian hostility, and the role political and religious elites play in this process. PI建议管理一系列家庭调查,以与什叶派宗教假期相吻合,以评估宗派紧张局势对民主,威权主义和极端主义的态度的因果关系。 此外,PI将利用实验设计来测试强调常见威胁和受害经历的程度,可能有两种方式减少逊尼派和什叶派穆斯林之间的外界偏见。 首先,通过对由学生组成的样本进行实验,其次,通过使用Twitter实验。通过采用创新的方法论方法,以基于和协调群体间关系的现有理论,该项目为政治学和社会心理学做出了重要贡献。 此外,通过帮助确定宗派敌意的原因和后果,并通过提供经验验证的方法来应对这种紧张局势,这项工作有望为政策制定者和学者提供宝贵的见解。

项目成果

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Joshua Tucker其他文献

Manufacturing Autoclave-Grade Thermoset Carbon Fiber-Reinforced Polymer Aerospace Composites without an Autoclave Using Nanoporous Materials.
使用纳米多孔材料无需高压釜即可制造高压釜级热固性碳纤维增强聚合物航空航天复合材料。
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    9.5
  • 作者:
    C. Li;Travis J. Hank;E. Kalfon;C. Furtado;Jeonyoon Lee;Shannon Cassady;Joshua Tucker;Seth S Kessler;B. Wardle
  • 通讯作者:
    B. Wardle

Joshua Tucker的其他文献

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{{ truncateString('Joshua Tucker', 18)}}的其他基金

RCN: Democracy in the Networked Era
RCN:网络时代的民主
  • 批准号:
    2331641
  • 财政年份:
    2023
  • 资助金额:
    $ 2.36万
  • 项目类别:
    Standard Grant
Lessons Learned: Navigating a Presidential Election During a Pandemic
经验教训:大流行期间的总统选举
  • 批准号:
    2104209
  • 财政年份:
    2021
  • 资助金额:
    $ 2.36万
  • 项目类别:
    Standard Grant
RAPID: Measuring Information Consumption and Beliefs During the Covid-19 Pandemic.
RAPID:衡量 Covid-19 大流行期间的信息消费和信念。
  • 批准号:
    2029610
  • 财政年份:
    2020
  • 资助金额:
    $ 2.36万
  • 项目类别:
    Standard Grant
Theory, Methods, and Empirical Analysis of Internet Bots
互联网机器人的理论、方法和实证分析
  • 批准号:
    1756657
  • 财政年份:
    2018
  • 资助金额:
    $ 2.36万
  • 项目类别:
    Standard Grant
Doctoral Dissertation Research in Political Science: Corruption and Incumbency Disadvantage in New Democracies
政治学博士论文研究:新民主国家的腐败和在职劣势
  • 批准号:
    1323034
  • 财政年份:
    2014
  • 资助金额:
    $ 2.36万
  • 项目类别:
    Standard Grant

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细粒度与个性化的学生议论文评价方法研究
  • 批准号:
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