Network polarization, filter bubbles, and echo chambers: an annotated review of measures and reduction methods
| Autor: | Ruben Interian, Ruslán G. Marzo, Isela Mendoza, Celso C. Ribeiro |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences J.4 Strategy and Management Computer Science - Social and Information Networks G.2.2 Management Science and Operations Research Computer Science Applications Computer Science - Computers and Society Management of Technology and Innovation Computers and Society (cs.CY) 05C69 05C90 Business and International Management |
| Zdroj: | International Transactions in Operational Research. |
| ISSN: | 1475-3995 0969-6016 |
| DOI: | 10.1111/itor.13224 |
| Popis: | 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. Corrected a typo in Section 3.2; the rest remains unchanged |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text