The ubiquitous availability of information in the age of social media and the increasing personalization of information flows are often alleged to contribute to the emergence of "filter bubbles" and “echo chambers”. In our triple-filter-bubble model (Geschke, Lorenz, & Holtz, 2019), we formalize filtering processes on three different levels: Algorithms, group processes, and individual cognitive and motivational processes. We used the NetLogo (Wilesky, 1999) agent-based modeling environment to analyze twelve different information filtering scenarios to answer the question under which circumstances social media and automatic recommender algorithms are most likely to contribute to fragmentation of modern society. We found that echo chambers can emerge as a consequence of cognitive mechanisms (e.g., confirmation bias) alone under certain conditions. When social and technological filtering mechanisms are added to the model, polarization of society into even more distinct and less interconnected echo chambers can be observed.