Social influence and unfollowing accelerate the emergence of echo chambers
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Social influence and unfollowing accelerate the emergence of echo chambers Kazutoshi Sasahara1,2,3 · Wen Chen3,4 · Hao Peng4,5 · Giovanni Luca Ciampaglia6,7 · Alessandro Flammini3,4,6 · Filippo Menczer3,4,6 Received: 8 December 2019 / Accepted: 20 August 2020 © The Author(s) 2020
Abstract While social media make it easy to connect with and access information from any‑ one, 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 dynam‑ ics show that even with minimal amounts of influence and unfriending, the social network rapidly devolves into segregated, homogeneous communities. These predic‑ tions 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
* Kazutoshi Sasahara sasahara@nagoya‑u.jp 1
Graduate School of Informatics, Nagoya University, Nagoya, Japan
2
JST PRESTO, Saitama, Japan
3
Center for Complex Networks and Systems Research, Indiana University Bloomington, Bloomington, USA
4
Luddy School of Informatics, Computing, and Engineering, Indiana University, Bloomington, USA
5
School of Information, University of Michigan, Ann Arbor, USA
6
Network Science Institute, Indiana University, Bloomington, USA
7
Department of Computer Science and Engineering, University of South Florida, Tampa, USA
13
Vol.:(0123456789)
Journal of Computational Social Science
Introduction The rise of social media has led to unprecedented changes in the scale and speed at which people share information. Social media feeds are key tools for accessing high volumes of news, opinions, and public information. However, just by foster‑ ing such a proliferation of information to which people are exposed, social media may interfere with cognitive selection biases, amplifying undesirable phenomena such as extremism and the spread of misinformation [1]. Further, they may intro‑ duce new biases in the way people consume information and form beliefs, which are not well understood yet. Theories about group decision-making and problem-solving suggest that aggregating knowledge, insights, or expertise from a diverse group of people is an effective strategy to solve complex problems, a notion called collective intel‑ ligence [2, 3]. While the Web and social media have often been hailed as striking examples of this principle in action [4, 5], some of the assumptions upon which these systems are predicated may harm the very diversity that makes them pre‑ cious
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