The echo chamber effect on social media

By Matteo Cinelli, Gianmarco De Francisci Morales, Alessandro Galeazzi, Walter Quattrociocchi, Michele Starnini. Proceedings of the National Academy of Sciences of the United States of America, 2021

1,839 citations recorded by the source corpus.

Significance We explore the key differences between the main social media platforms and how they are likely to influence information spreading and the formation of echo chambers. To assess the different dynamics, we perform a comparative analysis on more than 100 million pieces of content concerning controversial topics (e.g., gun control, vaccination, abortion) from Gab, Facebook, Reddit, and Twitter. The analysis focuses on two main dimensions: 1) homophily in the interaction networks and 2) bias in the information diffusion toward like-minded peers. Our results show that the aggregation in homophilic clusters of users dominates online dynamics. However, a direct comparison of news consumption on Facebook and Reddit shows higher segregation on Facebook. Social media may limit the exposure to diverse perspectives and favor the formation of groups of like-minded users framing and reinforcing a shared narrative, that is, echo chambers. However, the interaction paradigms among users and feed algorithms greatly vary across social media platforms. This paper explores the key differences between the main social media platforms and how they are likely to influence information spreading and echo chambers’ formation. We perform a comparative analysis of more than 100 million pieces of content concerning several controversial topics (e.g., gun control, vaccination, abortion) from Gab, Facebook, Reddit, and Twitter. We quantify echo chambers over social media by two main ingredients: 1) homophily in the interaction networks and 2) bias in the information diffusion toward like-minded peers. Our results show that the aggregation of users in homophilic clusters dominate online interactions on Facebook and Twitter. We conclude the paper by directly comparing news consumption on Facebook and Reddit, finding higher segregation on Facebook.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/67820785cf3c849fce6ba1e401ab3e1c231c7e73

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Citations in the corpus

Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts (2021, background): “This trend could be explained by the tendency of social- media users to form echo-chambers (Cinelli et al., 2021; Soliman et al., 2019).”
Growing polarization around climate change on social media (2021, background): “The appearance of two clusters with minimal inter-cluster density reveals the presence of “echo chambers” on social media [21], an environment in which users reinforce their opinions through repeated interactions with content adherent to their beliefs [21].”
Co-Writing with Opinionated Language Models Affects Users’ Views (2023, background): “Even without being designed to shift opinions, it has been found that algorithms may contribute to political polarization by reinforcing divisive opinions [9, 24, 32].”
Investigating social alignment via mirroring in a system of interacting language models (2024, unknown): “Similarly, (Carlson and Knoester, 2011) and (Cinelli et al., 2021) discuss potential causes of the formation of physical and online echo chambers.”