ArticleProceedings of the National Academy of Sciences of the United States of America2021
Polarized information ecosystems can reorganize social networks via information cascades.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- From the Selfish Gene to the "We": Cooperation Often Needs Suppressors.BioEssays : news and reviews in molecular, cellular and developmental biology · 2026Review
- Quantum-Tunnelling Oscillators for Cognitive Modelling and Neural Computation: Foundations, Machine-Vision Realisation and Applications.Entropy (Basel, Switzerland) · 2026Article
- United or Divided? A Polarized Society's Response to War.Public opinion quarterly · 2026Article
- Learned Insignificance of Credibility Signs.Cognitive science · 2025Article
- Our changing information ecosystem for science and why it matters for effective science communication.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- How opinion variation among in-groups can skew perceptions of ideological polarization.PNAS nexus · 2025Article
- Emergent structures of attention on social media are driven by amplification and triad transitivity.PNAS nexus · 2025Article
- How out-group animosity can shape partisan divisions: A model of affective polarization.PNAS nexus · 2025Article
- Patterns of partisan toxicity and engagement reveal the common structure of online political communication across countries.Nature communications · 2024Article
- An integrated empirical and computational study to decipher help-seeking behaviors and vocal stigma.Communications medicine · 2024Article
- Article
- Anticonformists catalyze societal transitions and facilitate the expression of evolving preferences.PNAS nexus · 2024Article
- Temporal dynamics of coordinated online behavior: Stability, archetypes, and influence.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- The functional aspects of selective exposure for collective decision-making under social influence.Scientific reports · 2024Article
- Containing misinformation: Modeling spatial games of fake news.PNAS nexus · 2024Article
- The limits of personal experience.Frontiers in psychology · 2024Article
- Discovery and characterisation of socially polarised communities on social media.Scientific reports · 2023Article
- Graph Representation Learning and Its Applications: A Survey.Sensors (Basel, Switzerland) · 2023Review
- How digital media drive affective polarization through partisan sorting.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Echo chambers and information transmission biases in homophilic and heterophilic networks.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The precise mechanisms by which the information ecosystem polarizes society remain elusive. Focusing on political sorting in networks, we develop a computational model that examines how social network structure changes when individuals participate in information cascades, evaluate their behavior, and potentially rewire their connections to others as a result. Individuals follow proattitudinal information sources but are more likely to first hear and react to news shared by their social ties and only later evaluate these reactions by direct reference to the coverage of their preferred source. Reactions to news spread through the network via a complex contagion. Following a cascade, individuals who determine that their participation was driven by a subjectively "unimportant" story adjust their social ties to avoid being misled in the future. In our model, this dynamic leads social networks to politically sort when news outlets differentially report on the same topic, even when individuals do not know others' political identities. Observational follow network data collected on Twitter support this prediction: We find that individuals in more polarized information ecosystems lose cross-ideology social ties at a rate that is higher than predicted by chance. Importantly, our model reveals that these emergent polarized networks are less efficient at diffusing information: Individuals avoid what they believe to be "unimportant" news at the expense of missing out on subjectively "important" news far more frequently. This suggests that "echo chambers"-to the extent that they exist-may not echo so much as silence.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.