As a lot of communication and media consumption moves online, people may be exposed to a wider population and more diverse opinions. However, individuals may act differently when faced with opinions far removed from their own. Moreover, changes in the frequency of visits, posting, and other forms of expression could lead to narrowing of the opinions that each person observes, as well as changes in the customer base for online platforms. Despite increasing research on the rise and fall of online social media outlets, user activity in response to exposure to others’ opinions has received little attention. In this study, we first introduce a method that maps opinions of individuals and their generated content on a multi-dimensional space by factorizing an individual–object interaction (e.g., user-news rating) matrix. Using data on 6151 users interacting with 287,327 pieces of content over 21 months on a social media platform we estimate changes in individuals’ activities in response to interaction with content expressing a variety of opinions. We find that individuals increase their online activities when interacting with content close to their own opinions, and interacting with extreme opinions may decrease their activities. Finally, developing an agent-based simulation model, we study the effect of the estimated mechanisms on the future success of a simulated platform.