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People Politics. Exploring the link between populist rhetoric, institutional representation and far right mobilisation

人民政治。

基本信息

批准号：
1923683
负责人：
金额：
--
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1923683
关键词：
People Politics.Exploring link between

项目摘要

This study will focus on reconceptualising the role of political opportunities in understanding mobilisation patterns. Political engagement is generally thought to decrease levels of extra-institutional violence (Kriesi et al, 1995). As violent behaviour is associated with high risks for the aggressor, its occurrence hinges on the existence of legitimate channels to pressure political elites. This theory is in line with research on ethnic violence in Germany (Braun and Koopmans; 2014; Grund, 2011; Koopmans and Olzak, 2004), which find that violence is less likely in communities with strong right-extremist party support.I aim to specifically analyse the relationship between political representation and extra-institutional mobilisation. By defining populism as a discursive strategy instead of as a stable ideological attribute, it may be possible to analyse how changes in political rhetoric influence far right mobilisation patterns (see Bonikowski and Gidron 2016). I will additionally aim to quantify parties' willingness to excuse or encourage right-extremist violent acts by applying cutting-edge computational text analysis to political corpora. In doing so, I hope to get a more realistic grasp on how politicians and their reactions to violent events influence diffusion patterns of ethnic conflict, and, more generally, explore the intricate relationship between institutional representation and extra-institutional mobilisation.My proposed research topic consists of three main components. The first part will focus on continuing my MSc Dissertation project, expanding the dataset and looking at a wider set of questions. By including other forms of politically motivated crimes, it will be possible to widen the scope of the paper to explore whether motivations for criminal behaviour differ according to the severity of the offense. As violent events are temporally clustered and non-randomly distributed across Germany, the study seeks to map the diffusion processes of ethnic conflict across the country, using event history analyses and panel regression models. Increasing the number of cases will also allow a more rigorous analysis of the difference between official and independent statistics, in order to reveal which factors make the registration of a right extremist crime as "politically-motivated" more likely.The second part of my research project will explore the dynamics of populist claim-making in German politics. By operationalizing populism as a discursive strategy, where the interests of a virtuous populace are juxtaposed with those of corrupt elites, it is possible to analyse variations in the occurrence of populism within parties and politicians, focusing specifically on populist rhetoric centred around migration debates. Following Bonikowski and Gidron (2016), I plan on applying dictionary-based automated text analysis to the study of political corpora. Sociologists have counted statements as reported in newspapers, but digital text analysis enables us to capitalise on the rise of the Internet and the flood of textual data, and quantify dynamics that were previously thought to be impossible to analyse. A computational data approach would shed light on the content of far-right populist discourse, and may show whether the usage of populist claims corresponds to current socio-economic and demographic contexts.In the final part of the D.Phil. research project, I aim to combine the approaches in the first two chapters to explore how variations in right populist rhetoric influence mobilisation processes. Combining computational text analysis with event history models of right-extremist crimes, I also aim to identify politicians' roles in mediating the diffusion of violent events to their constituency. Does the way far right politicians' react to violent events have an influence on their subsequent diffusion?

这项研究将侧重于重新概念化的政治机会在理解动员模式的作用。人们普遍认为，政治参与可以减少体制外暴力的程度（Kriesi等人，1995年）。由于暴力行为与侵犯者的高风险有关，其发生取决于是否存在向政治精英施压的合法渠道。这一理论与关于德国种族暴力的研究（Braun and Koopmans; 2014; Grund，2011; Koopmans and Olzak，2004）相一致，该研究发现，在右翼极端主义政党支持强大的社区，暴力发生的可能性较小。通过将民粹主义定义为一种话语策略，而不是一种稳定的意识形态属性，也许可以分析政治言论的变化如何影响极右翼的动员模式（见Bonikowski和Gidron 2016）。此外，我还将通过对政治语料库进行尖端的计算文本分析，量化政党原谅或鼓励右翼极端主义暴力行为的意愿。在这样做的时候，我希望得到一个更现实的把握如何政治家和他们的反应，暴力事件的影响种族冲突的扩散模式，更一般地说，探索机构代表性和机构外动员之间的错综复杂的关系。我提出的研究课题包括三个主要组成部分。第一部分将专注于继续我的硕士论文项目，扩展数据集并查看更广泛的问题集。通过列入其他形式的出于政治动机的犯罪，将有可能扩大本文件的范围，探讨犯罪行为的动机是否因罪行的严重程度而异。由于暴力事件在时间上是集群的，非随机分布在德国，该研究旨在映射全国各地的种族冲突的扩散过程，使用事件历史分析和面板回归模型。增加案件数量还可以更严格地分析官方和独立统计数据之间的差异，以揭示哪些因素使右翼极端主义犯罪更有可能被登记为“政治动机”。我的研究项目的第二部分将探讨德国政治中民粹主义主张的动态。通过将民粹主义作为一种话语战略来运作，将善良民众的利益与腐败精英的利益并列，可以分析政党和政治家内部民粹主义发生的变化，特别关注围绕移民辩论的民粹主义言论。继Bonikowski和Gidron（2016）之后，我计划将基于词典的自动文本分析应用于政治语料库的研究。社会学家已经统计了报纸上报道的声明，但数字文本分析使我们能够利用互联网的兴起和文本数据的泛滥，并量化以前被认为是不可能分析的动态。计算数据的方法将揭示极右翼民粹主义话语的内容，并可能显示民粹主义主张的使用是否符合当前的社会经济和人口背景。作为一个研究项目，我的目标是将前两章的方法联合收割机结合起来，探索右翼民粹主义言论的变化如何影响动员过程。将计算文本分析与右翼极端主义犯罪的事件历史模型相结合，我还旨在确定政治家在调解暴力事件向其选区扩散中的作用。极右翼政客对暴力事件的反应方式是否会影响其随后的传播？