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arxiv: 1905.03919 · v3 · pith:Y4C4JU5Fnew · submitted 2019-05-10 · 💻 cs.CY · cs.SI· physics.soc-ph

Social Influence and Unfollowing Accelerate the Emergence of Echo Chambers

classification 💻 cs.CY cs.SIphysics.soc-ph
keywords socialchambersechoinfluenceinformationtheyunfriendingmechanisms
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While social media make it easy to connect with and access information from anyone, they also facilitate basic influence and unfriending mechanisms that may lead to segregated and polarized clusters known as "echo chambers." Here we study the conditions in which such echo chambers emerge by introducing a simple model of information sharing in online social networks with the two ingredients of influence and unfriending. Users can change both their opinions and social connections based on the information to which they are exposed through sharing. The model dynamics show that even with minimal amounts of influence and unfriending, the social network rapidly devolves into segregated, homogeneous communities. These predictions are consistent with empirical data from Twitter. Although our findings suggest that echo chambers are somewhat inevitable given the mechanisms at play in online social media, they also provide insights into possible mitigation strategies.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Inside the Echo Chamber: Disentangling network dynamics from polarization

    physics.soc-ph 2019-06 unverdicted novelty 5.0

    Temporal network analysis of Twitter data shows echo chamber strength declining due to rising cross-opinion interactions, with polarization and network dynamics evolving independently.