Computational methods offer a new perspective on the evolving agendas of right-wing movements and parties online. This article showcases computational approaches to text analysis (specifically so-called topic models) to diachronically investigate nativist right-wing issues in social media by comparing comments posted on the Facebook page of the Pegida movement to those of the Alternative for Germany. After describing topic modelling as an increasingly popular method and drawing on the literature on right-wing nativism online, we investigate a set of shared issues relevant to the mobilization of commentators, including opposition to Islam, migration, the government and the media. We furthermore show contrastively how issue prevalence differs between the two groups, and how issue shares change over time, in some instances converging on a shared nativist core. We close with a series of suggestions on the utility of computation content analysis for the study of rapidly evolving political agendas.

中文翻译：

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收敛于本土主义核心？比较 Pegida 运动和德国替代方案 Facebook 页面上的问题

计算方法为右翼运动和在线政党不断发展的议程提供了新的视角。本文展示了文本分析的计算方法（特别是所谓的主题模型），通过比较 Pegida 运动 Facebook 页面上发布的评论与德国替代方案的评论，历时调查社交媒体中的本土主义右翼问题。在将话题建模描述为一种日益流行的方法并借鉴网上关于右翼本土主义的文献后，我们调查了一系列与动员评论员相关的共同问题，包括反对伊斯兰教、移民、政府和媒体。我们还对比展示了两组之间的发行流行率如何不同，以及发行份额如何随时间变化，在某些情况下，会聚在一个共享的本土主义核心上。我们最后提出了一系列关于计算内容分析在研究快速发展的政治议程方面的效用的建议。