Social media and data mining are increasingly being used to analyze political and societal issues. Here, we undertake the classification of social media users as supporting or opposing ongoing independence movements in their territories. Independence movements occur in territories whose citizens have conflicting national identities; users with opposing national identities will then support or oppose the sense of being part of an independent nation that differs from the officially recognized country. We describe a methodology that relies on users’ self-reported location to build large-scale datasets for three territories—Catalonia, the Basque Country, and Scotland. An analysis of these datasets shows that homophily plays an important role in determining who people connect with, as users predominantly choose to follow and interact with others from the same national identity. We show that a classifier relying on users’ follow networks can achieve accurate, language-independent classification performances ranging from 85% to 97% for the three territories.

中文翻译：

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独立运动中的政治同质性：按国家身份分析和分类社交媒体用户

社交媒体和数据挖掘越来越多地用于分析政治和社会问题。在这里，我们将社交媒体用户分类为支持或反对其领土内正在进行的独立运动。独立运动发生在公民具有相互冲突的民族认同的领土上；具有相反民族身份的用户将支持或反对成为与官方认可的国家不同的独立国家的一部分的感觉。我们描述了一种方法，该方法依赖于用户自我报告的位置来为三个地区（加泰罗尼亚、巴斯克地区和苏格兰）构建大规模数据集。对这些数据集的分析表明，同质性在确定人们与谁联系方面起着重要作用，因为用户主要选择关注具有相同国家身份的其他人并与之互动。我们表明，依赖于用户关注网络的分类器可以在三个地区实现准确的、独立于语言的分类性能，范围从 85% 到 97%。