Homophily -- our tendency to surround ourselves with others who share our perspectives and opinions about the world -- is both a part of human nature and an organizing principle underpinning many of our digital social networks. However, when it comes to politics or culture, homophily can amplify tribal mindsets and produce "echo chambers" that degrade the quality, safety, and diversity of discourse online. While several studies have empirically proven this point, few have explored how making users aware of the extent and nature of their political echo chambers influences their subsequent beliefs and actions. In this paper, we introduce Social Mirror, a social network visualization tool that enables a sample of Twitter users to explore the politically-active parts of their social network. We use Social Mirror to recruit Twitter users with a prior history of political discourse to a randomized experiment where we evaluate the effects of different treatments on participants' i) beliefs about their network connections, ii) the political diversity of who they choose to follow, and iii) the political alignment of the URLs they choose to share. While we see no effects on average political alignment of shared URLs, we find that recommending accounts of the opposite political ideology to follow reduces participants' beliefs in the political homogeneity of their network connections but still enhances their connection diversity one week after treatment. Conversely, participants who enhance their belief in the political homogeneity of their Twitter connections have less diverse network connections 2-3 weeks after treatment. We explore the implications of these disconnects between beliefs and actions on future efforts to promote healthier exchanges in our digital public spheres.
翻译:与分享我们对世界的看法和看法的其他人一起环绕我们的倾向 -- -- 我们倾向于与其它人环绕着我们自己,这既是人性的一部分,也是支撑我们许多数字社会网络的组织原则。然而,在政治或文化方面,同质可以扩大部落的心态,并产生降低在线谈话质量、安全和多样性的“分室 ” 。虽然一些研究从经验上证明了这一点,但很少有人探索如何让用户了解其政治回声回声室的范围和性质如何影响他们后来的信仰和行动。在本文中,我们引入了社会镜(Scial Mirror),这是一个社交网络的视觉化工具,让一个推特用户样本能够探索其社会网络中政治活跃的部分。我们利用社会镜(Scial Mirrority)招募具有以往政治讨论史的推特用户,以随机化实验的方式评估不同待遇对参与者网络联系的影响,二)他们选择追随者的政治多样性的政治多样性的多样性,三)他们选择分享的网络的政治一致性。我们看到对共同URL的平均政治一致性没有影响,但我们仍然建议对政治意识形态的对比进行描述,但建议采用相反的政治意识形态,从而降低他们未来两派网络之间的联系。