Our article describes how users’ decisions to share content alter the frequencies of the frame elements observed by social media peers. Changes in the frequency of distinct frame elements shape how individuals interpret, classify and define situations and events. We label this process Network Activated Frames (NAFs). We test the mechanisms behind NAF with an original image-based conjoint design that replicates network activation in three surveys. Results show that partisans share more content than nonpartisans and that their preferences differ from those of nonpartisans. Our findings show that a network of peers with cross-cutting ideological preferences may be perceived as a bubble if partisans amplify content they like at higher rates. Beginning with fully randomized probabilities, the output from our experiments is more extreme than the preferences of the median users, as partisans activate more and different frame elements than nonpartisans. We implement the experiments in Argentina, Brazil, and Mexico.