Polarization arises when the underlying network connecting the members of a
community or society becomes characterized by highly connected groups with weak
inter-group 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, 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.Comment: Corrected a typo in Section 3.2; the rest remains unchange