用 Reddit 政治罗盘导航多维意识形态：经济冲突与社会亲和
Navigating Multidimensional Ideologies with Reddit's Political Compass: Economic Conflict and Social Affinity
AI总结：
本研究利用 Reddit 政治罗盘子版块超 800 万条评论，将用户意识形态分解为经济轴与社会轴，发现社会轴及人口属性上存在同质性互动，而经济轴上存在异质性互动且语言毒性更高，从而调和了在线政治讨论中同质与异质互动并存的矛盾。
摘要：
在意见动力学的定量研究中，主流视角将在线政治话语的图景扁平化为传统的左—右二分法。虽然这种方法有助于简化分析和建模工作，但它也忽略了意识形态内在的多维丰富性。在本研究中，我们在多维意识形态框架——政治罗盘——的视角下分析 Reddit 上的社会互动。我们考察了 2020 至 2022 年间发布在 /r/PoliticalCompass 和 /r/PoliticalCompassMemes 子版块上的超过 800 万条评论。通过利用用户的自我声明，我们将用户的意识形态维度分解为经济（左—右）轴和社会（自由意志主义—威权主义）轴。此外，我们还通过人口统计学属性（年龄、性别和富裕程度）来刻画用户。我们发现，沿着政治罗盘的社会轴以及人口统计学属性，互动存在显著的同质性。与零模型相比，相似意识形态个体之间的互动超出预期 6%。相比之下，我们揭示了经济轴上显著的异质性：左/右互动超出预期 10%。此外，异质性互动的特点是语言毒性高于同质性互动，这暗示着每一种对立意识形态之间存在冲突性话语。我们的结果有助于调和近期文献中明显的矛盾，这些文献发现在线政治讨论中同质性和异质性互动同时存在。通过将这类互动分解为经济轴和社会轴，我们为更深入地理解社交媒体上的意见动力学铺平了道路。
英文摘要：
The prevalent perspective in quantitative research on opinion dynamics flattens the landscape of the online political discourse into a traditional left--right dichotomy. While this approach helps simplify the analysis and modeling effort, it also neglects the intrinsic multidimensional richness of ideologies. In this study, we analyze social interactions on Reddit, under the lens of a multi-dimensional ideological framework: the political compass. We examine over 8 million comments posted on the subreddits /r/PoliticalCompass and /r/PoliticalCompassMemes during 2020--2022. By leveraging their self-declarations, we disentangle the ideological dimensions of users into economic (left--right) and social (libertarian--authoritarian) axes. In addition, we characterize users by their demographic attributes (age, gender, and affluence). We find significant homophily for interactions along the social axis of the political compass and demographic attributes. Compared to a null model, interactions among individuals of similar ideology surpass expectations by 6%. In contrast, we uncover a significant heterophily along the economic axis: left/right interactions exceed expectations by 10%. Furthermore, heterophilic interactions are characterized by a higher language toxicity than homophilic interactions, which hints at a conflictual discourse between every opposite ideology. Our results help reconcile apparent contradictions in recent literature, which found a superposition of homophilic and heterophilic interactions in online political discussions. By disentangling such interactions into the economic and social axes we pave the way for a deeper understanding of opinion dynamics on social media.
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