Network polarization, filter bubbles, and echo chambers: an annotated review of measures and reduction methods

Abstract

Polarization arises when the underlying network connecting the members of a community or society becomes characterized by highly connected groups with weak intergroup connectivity. The increasing polarization, the strengthening of echo chambers, and the isolation caused by information filters in social networks are increasingly attracting the attention of researchers from different areas of knowledge such as computer science, economics, and social and political sciences. This work presents an annotated review of network polarization measures and models used to handle the polarization. Several approaches for measuring polarization in graphs and networks were identified, including those based on homophily, modularity, random walks, and balance theory. The strategies used for reducing polarization include methods that propose edge or node editions (including insertions or deletions as well as edge weight modifications), changes in social network design, or changes in the recommendation systems embedded in these networks.