Humanity for centuries has perfected skills of interpersonal interactions and evolved patterns that enable people to detect lies and deceiving behavior of others in face-to-face settings. Unprecedented growth of people's access to mobile phones and social media raises an important question: How does this new technology influence people's interactions and support the use of traditional patterns? In this paper, we answer this question for homophily driven patterns in social media. In our previous studies, we found that, on a university campus, changes in student opinions were driven by the desire to hold popular opinions. Here, we demonstrate that the evolution of online platform-wide opinion groups is driven by the same desire. We focus on two social media: Twitter and Parler, on which we tracked the political biases of their users. On Parler, an initially stable group of right-biased users evolved into a permanent right-leaning echo chamber dominating weaker, transient groups of members with opposing political biases. In contrast, on Twitter, the initial presence of two large opposing bias groups led to the evolution of a bimodal bias distribution, with a high degree of polarization. We capture the movement of users from the initial to final bias groups during the tracking period. We also show that user choices are influenced by side-effects of homophily. The users entering the platform attempt to find a sufficiently large group whose members hold political bias within the range sufficiently close to the new user's bias. If successful, they stabilize their bias and become a permanent member of the group. Otherwise, they leave the platform. We believe that the dynamics of users uncovered in this paper create a foundation for technical solutions supporting social groups on social media and socially aware networks.

翻译：人类历经数个世纪完善了人际互动的技能，并演化出使人们能够在面对面情境中察觉他人谎言与欺骗行为的模式。人们接触手机和社交媒体的机会空前增长，这引发了一个重要问题：这种新技术如何影响人们的互动，并支持传统模式的应用？在本文中，我们针对社交媒体中由同质性驱动的模式回答了这一问题。在先前的研究中，我们发现大学校园内学生观点的变化受持受欢迎观点欲望的驱动。在此，我们证明在线平台范围内观点群体的演化同样受这一欲望驱动。我们聚焦于两个社交媒体平台：Twitter和Parler，追踪了其用户的政治偏见。在Parler上，起初由右倾用户组成的稳定群体演化成了一个永久性的右倾回音室，主导了拥有对立政治偏见的较弱势、临时性的成员群体。相比之下，在Twitter上，最初两个大型对立偏见群体的存在导致了双峰式偏见分布的演化，呈现出高度的两极分化。我们捕捉了追踪期间用户从初始偏见群体向最终偏见群体的迁移过程。我们还表明，用户的选择受到同质性副作用的影响。进入平台的用户试图寻找一个足够大的群体，其成员所持政治偏见与新用户偏见的范围足够接近。若成功，他们便会稳定自身偏见并成为该群体的永久成员；否则，他们会离开平台。我们相信，本文揭示的用户动态为支持社交媒体及社交感知网络上的社会群体提供了技术解决方案的基础。