Echo Chambers on Facebook

By Walter Quattrociocchi, Antonio Scala, Cass R. Sunstein. 2016

365 citations recorded by the source corpus.

Subfields: Communication, General Social Sciences

View Paper: https://www.semanticscholar.org/paper/fc8c011c18bba6f8056f8c51510560bc32897353

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In Communication

In General Social Sciences

Kai Shu

Citations in the corpus

Echo chambers and viral misinformation: Modeling fake news as complex contagion (2018, background): “A polarized digital space where users tend to promote their favorite narratives, form polarized groups and resist information that does not conform to their beliefs may be the fertilizer that makes the Internet so fertile for the growth of misinformation [20].”
Stance Detection on Social Media: State of the Art and Trends (2020, background): “tforms are echo-chambers and homophily [Fuchs 2017]. Previous studies have concluded that social media are polarized in nature which boost homophily behavior [Barber´a et al. 2015; Bessi et al. 2016; Quattrociocchi et al. 2016; Darwish et al. 2017a; Garimella et al. 2018]. Homophily is the social ph”
Fake News Detection on Social Media: A Data Mining Perspective (2017, background): “e psychological challenges to dispelling fake news identied above. For example, users on Facebook always follow like-minded people and thus receive news that promote their favored existing narratives [65]. Therefore, users on social media tend to form groups containing like-minded people where they ”
Combating Fake News (2019, background): “Quattrociocchi et al. 2016 similarly studied polarization by scientific v/s conspiracy narratives in Facebook users and observed that although both types of information were consumed similarly overall, 76.79% of all users who interacted on scientific pages and 91.53% of all users who interacted…”
Beyond News Contents: The Role of Social Context for Fake News Detection (2017, background): “example,u2 and u4 are users with low credibility scores, and they tend to spread fake news more than other highly credible users. In addition, users tend to form relationships with like-minded people [25]. For example, user u5 and u6 are friends on social media, so they tend to post those news that ”
Political Discourse on Social Media: Echo Chambers, Gatekeepers, and the Price of Bipartisanship (2018, background): “s that have studied echo chambers under different perspectives. For instance, previous works have focused either on the differences between the content shared and read by partisans of different sides [3, 20, 21, 35]; the social network structure [23]; or the structure of user interactions, such as b”
The echo chamber effect on social media (2021, background): “Echo chambers have been shown to exist in various forms of online media such as blogs (24), forums (25), and social media sites (26–28).”
Fake News and The Economy of Emotions (2018, background): “Empirically demonstrated consequences of algorithmically created filter bubbles and human confirmation bias are limited exposure to, and lack of engagement with, different ideas and other people’s viewpoints (Bessi et al. 2016; Quattrociocchi et al. 2016).”