  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 article, 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. Users
entering the platform attempt to find a sufficiently large group whose members
hold political biases within the range sufficiently close to their own. If
successful, they stabilize their biases and become permanent members of the
group. Otherwise, they leave the platform. We believe that the dynamics of
users' behavior uncovered in this article create a foundation for technical
solutions supporting social groups on social media and socially aware networks.
