Social influence and unfollowing accelerate the emergence of echo chambers

Kazutoshi Sasahara (), Wen Chen, Hao Peng, Giovanni Luca Ciampaglia, Alessandro Flammini and Filippo Menczer
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Kazutoshi Sasahara: Nagoya University
Wen Chen: Indiana University Bloomington
Hao Peng: Indiana University
Giovanni Luca Ciampaglia: Indiana University
Alessandro Flammini: Indiana University Bloomington
Filippo Menczer: Indiana University Bloomington

Journal of Computational Social Science, 2021, vol. 4, issue 1, No 15, 402 pages

Abstract: Abstract 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.

Keywords: Echo Chamber; Opinion dynamics; Social media; Social network (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s42001-020-00084-7

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