We evaluate homophily and heterophily among ideological and demographic groups in a typical opinion formation context: online discussions of current news. We analyze user interactions across five years in the r/news community on Reddit, one of the most visited websites in the United States. Then, we estimate demographic and ideological attributes of these users. Thanks to a comparison with a carefully-crafted network null model, we establish which pairs of attributes foster interactions and which ones inhibit them. Individuals prefer to engage with the opposite ideological side, which contradicts the echo chamber narrative. Instead, demographic groups are homophilic, as individuals tend to interact within their own group - even in an online setting where such attributes are not directly observable. In particular, we observe age and income segregation consistently across years: users tend to avoid interactions when belonging to different groups. These results persist after controlling for the degree of interest by each demographic group in different news topics. Our findings align with the theory that affective polarization - the difficulty in socializing across political boundaries-is more connected with an increasingly divided society, rather than ideological echo chambers on social media. We publicly release our anonymized data set and all the code to reproduce our results: https://github.com/corradomonti/demographic-homophily

翻译：我们评估了典型舆论形成情境（即当前新闻的在线讨论）中意识形态和人口群体之间的同质性与异质性。我们分析了Reddit上r/news社区（美国访问量最大的网站之一）五年间的用户交互行为，并估算了这些用户的人口统计学和意识形态属性。通过精心构建的网络零模型进行对比，我们确定了哪些属性组合促进互动、哪些抑制互动。研究显示，个体更倾向于与对立意识形态方互动，这与"回音室"叙事相悖；而人口统计学群体则呈现同质性——即便在属性不可直接观测的在线环境中，个体仍趋向于本群体内互动。具体而言，我们观察到年龄和收入隔离在多年间持续存在：不同群体的用户倾向于避免互动。在控制各人口群体对不同新闻话题的兴趣程度后，这一结果仍保持稳健。我们的发现与情感极化（跨政治边界社交的困难）与社会日益分裂相关而非社交媒体意识形态回音室的学说一致。我们已公开匿名化数据集及重现结果的完整代码：https://github.com/corradomonti/demographic-homophily