Departmental Papers (ASC)

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Journal Article

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Science Advances





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“Fake news,” broadly defined as deliberately false or misleading information masquerading as legitimate news, is frequently asserted to be pervasive on the web, and on social media in particular, with serious consequences for public opinion, political polarization, and ultimately democracy. Using a unique multimode data set that comprises a nationally representative sample of mobile, desktop, and television consumption across all categories of media content, we refute this conventional wisdom on three levels. First, news consumption of any sort is heavily outweighed by other forms of media consumption, comprising at most 14.2% of Americans’ daily media diets. Second, to the extent that Americans do consume news, it is overwhelmingly from television, which accounts for roughly five times as much as news consumption as online, while a supermajority of Americans consume little or no news online at all. Third, fake news comprises only about 1% of overall news consumption and 0.15% of Americans’ daily media diet. Although consumption data alone cannot determine that online misinformation in any dose is not dangerous to democracy, our results suggest that the origins of public mis-informedness and polarization are more likely to lie in the content of ordinary news--especially on television--or alternatively in the avoidance of news altogether as they are in overt fakery.

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Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license, which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.


Note: Currently, Dr. Duncan J. Watts is Stevens University Professor at the University of Pennsylvania, and Professor in Department of Computer and Information Science in the School of Engineering and Applied Science, Annenberg School for Communication, and Department of Operations, Information and Decisions in the Wharton School.

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Date Posted: 20 March 2023

This document has been peer reviewed.