This study tests a hypothesis that information sources (e.g., Facebook pages) that share information more frequently with each other have high level of audience overlapping. This association is also hypothesized to be politically motivated. To test the empirical relationship, a Facebook pages sharing network was created using the information shared between 1453 Facebook pages during a social movement in Hong Kong. The sharing frequency between two pages was denoted as the page-level edge weight. The audience of Facebook pages—commenters and likers of the page’s posts—were collected. The Jaccard similarity coefficient between two pages was measured as the audience-level edge weight. Using network regression analysis, the page-level and audience-level edge weights were significantly associated. To show this relationship is politically motivated, 1076 audience members were randomly selected and with their political preferences labeled by inferring from their Facebook profile pictures. Using machine learning models, the repertoires of Facebook pages that they have interacted with can predict their political preferences. Our study demonstrated that selective sharing between information source is associated with the division of their audiences into enclaved subgroups with similar political ideologies.
