Filter Bubbles, Echo Chambers, and Online News Consumption

Public Opinion Quarterly, Vol. 80, Special Issue, 2016, pp. 298–320

42 Pages Posted: 6 Dec 2013 Last revised: 27 Jul 2016

See all articles by Seth Flaxman

Seth Flaxman

Imperial College London - Department of Mathematics; Department of Statistics

Sharad Goel

Stanford University

Justin M. Rao

Microsoft Research; Microsoft Corporation - Microsoft Research - Redmond

Date Written: March 22, 2016

Abstract

Online publishing, social networks, and web search have dramatically lowered the costs of producing, distributing, and discovering news articles. Some scholars argue that such technological changes increase exposure to diverse perspectives, while others worry that they increase ideological segregation. We address the issue by examining webbrowsing histories for 50,000 US-located users who regularly read online news. We find that social networks and search engines are associated with an increase in the mean ideological distance between individuals. However, somewhat counterintuitively, these same channels also are associated with an increase in an individual's exposure to material from his or her less preferred side of the political spectrum. Finally, the vast majority of online news consumption is accounted for by individuals simply visiting the home pages of their favorite, typically mainstream, news outlets, tempering the consequences -- both positive and negative -- of recent technological changes. We thus uncover evidence for both sides of the debate, while also finding that the magnitude of the effects is relatively modest

Keywords: media economics, information acquisition, media bias, online behavior, big data, confirmation bias

JEL Classification: D83, L86, L82

Suggested Citation

Flaxman, Seth and Goel, Sharad and Rao, Justin M., Filter Bubbles, Echo Chambers, and Online News Consumption (March 22, 2016). Public Opinion Quarterly, Vol. 80, Special Issue, 2016, pp. 298–320, Available at SSRN: https://ssrn.com/abstract=2363701 or http://dx.doi.org/10.2139/ssrn.2363701

Seth Flaxman

Imperial College London - Department of Mathematics ( email )

South Kensington Campus
Imperial College
LONDON, SW7 2AZ
United Kingdom

Department of Statistics ( email )

24-29 St Giles'
Oxford, Oxfordshire OX1 3LB
United Kingdom

Sharad Goel (Contact Author)

Stanford University ( email )

475 Via Ortega
Stanford, CA 94305
United States

HOME PAGE: http://5harad.com

Justin M. Rao

Microsoft Research ( email )

641 Avenue of Americas
7th Floor
New York, NY 11249
United States

Microsoft Corporation - Microsoft Research - Redmond ( email )

Building 99
Redmond, WA
United States

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