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.

翻译：极化现象表现为连接社群或社会成员的底层网络呈现高度聚集的子群、且子群间连接薄弱。社交网络中日益加剧的极化趋势、回声室的强化以及信息过滤器造成的隔离现象，正引起计算机科学、经济学、社会科学与政治学等不同领域研究者的广泛关注。本文对用于处理极化问题的网络极化测度与模型进行评述，梳理了图与网络中多种极化测度方法，包括基于同质性、模块度、随机游走和平衡理论的方法。减少极化的策略涵盖边或节点编辑（含插入、删除及边权重调整）、社交网络设计变更，以及嵌入于这些网络的推荐系统调整。