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Geographic and Temporal Trends in Fake News Consumption During the 2016 US Presidential Election

Authors:

Eric HorvitzAuthors Info & Claims

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

Pages 2071 - 2074

https://doi.org/10.1145/3132847.3133147

Published: 06 November 2017 Publication History

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Abstract

We present an analysis of traffic to websites known for publishing fake news in the months preceding the 2016 US presidential election. The study is based on the combined instrumentation data from two popular desktop web browsers: Internet Explorer 11 and Edge. We find that social media was the primary outlet for the circulation of fake news stories and that aggregate voting patterns were strongly correlated with the average daily fraction of users visiting websites serving fake news. This correlation was observed both at the state level and at the county level, and remained stable throughout the main election season. We propose a simple model based on homophily in social networks to explain the linear association. Finally, we highlight examples of different types of fake news stories: while certain stories continue to circulate in the population, others are short-lived and die out in a few days.

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Cited By

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Rhodes S(2024)Narrow Margins and Misinformation: The Impact of Sharing Fake News in Close ContestsSocial Sciences10.3390/socsci1311057113:11(571)Online publication date: 24-Oct-2024
https://doi.org/10.3390/socsci13110571
Smith LThomas EBliuc AMcGarty C(2024)Polarization is the psychological foundation of collective engagementCommunications Psychology10.1038/s44271-024-00089-22:1Online publication date: 6-May-2024
https://doi.org/10.1038/s44271-024-00089-2
Nannini LBonel EBassi DMaggini M(2024)Beyond phase-in: assessing impacts on disinformation of the EU Digital Services ActAI and Ethics10.1007/s43681-024-00467-wOnline publication date: 11-Apr-2024
https://doi.org/10.1007/s43681-024-00467-w
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Index Terms

Geographic and Temporal Trends in Fake News Consumption During the 2016 US Presidential Election
1. Human-centered computing
  1. Collaborative and social computing
    1. Collaborative and social computing theory, concepts and paradigms
      1. Social media
2. Information systems
  1. World Wide Web
    1. Web mining
      1. Web log analysis

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Published In

CIKM '17: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management

November 2017

2604 pages

ISBN:9781450349185

DOI:10.1145/3132847

General Chairs:
Ee-Peng Lim
Singapore Management University, Singapore
,
Marianne Winslett
University of Illinois at Urbana-Champaign, USA, and Advanced Digital Sciences Center, Singapore
,
Program Chairs:
Mark Sanderson
RMIT, Australia
,
Ada Fu
Chinese University of Hong Kong, Hong Kong
,
Jimeng Sun
Georgia Tech, USA
,
Shane Culpepper
RMIT, Australia
,
Eric Lo
Chinese University of Hong Kong, Hong Kong
,
Joyce Ho
Emory University, USA
,
Debora Donato
Mix Tech, Inc., USA
,
Rakesh Agrawal
Data Insights Laboratories, USA
,
Yu Zheng
Microsoft Research Asia, China
,
Carlos Castillo
Qatar Computing Research Institute, Qatar
,
Aixin Sun
Nanyang Technological University, Singapore
,
Vincent S. Tseng
National Cheng Kung University, Taiwan
,
Chenliang Li
Wuhan University, China

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 06 November 2017

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November 6 - 10, 2017

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Cited By

View all

Rhodes S(2024)Narrow Margins and Misinformation: The Impact of Sharing Fake News in Close ContestsSocial Sciences10.3390/socsci1311057113:11(571)Online publication date: 24-Oct-2024
https://doi.org/10.3390/socsci13110571
Smith LThomas EBliuc AMcGarty C(2024)Polarization is the psychological foundation of collective engagementCommunications Psychology10.1038/s44271-024-00089-22:1Online publication date: 6-May-2024
https://doi.org/10.1038/s44271-024-00089-2
Nannini LBonel EBassi DMaggini M(2024)Beyond phase-in: assessing impacts on disinformation of the EU Digital Services ActAI and Ethics10.1007/s43681-024-00467-wOnline publication date: 11-Apr-2024
https://doi.org/10.1007/s43681-024-00467-w
Chen JZhou GLu JWang SLi S(2023)Trust-Aware Evidence Reasoning and Spatiotemporal Feature Aggregation for Explainable Fake News DetectionApplied Sciences10.3390/app1309570313:9(5703)Online publication date: 5-May-2023
https://doi.org/10.3390/app13095703
Zareer MSelmic R(2023)Modeling Control Agents in Social Media Networks Using Reinforcement LearningAdvances in Science, Technology and Engineering Systems Journal10.25046/aj0805078:5(62-69)Online publication date: Oct-2023
https://doi.org/10.25046/aj080507
Ferrucci PHopp T(2023)Let’s intervene: How platforms can combine media literacy and self-efficacy to fight fake newsCommunication and the Public10.1177/205704732312030818:4(367-389)Online publication date: 31-Oct-2023
https://doi.org/10.1177/20570473231203081
Sridhar ARouttenberg TPoor H(2023)Quickest Inference of Susceptible-Infected Cascades in Sparse Networks2023 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT54713.2023.10206471(102-107)Online publication date: 25-Jun-2023
https://doi.org/10.1109/ISIT54713.2023.10206471
Butts DBollman SMurillo M(2023)Mathematical modeling of disinformation and effectiveness of mitigation policiesScientific Reports10.1038/s41598-023-45710-213:1Online publication date: 31-Oct-2023
https://doi.org/10.1038/s41598-023-45710-2
Shahid FMare SVashistha A(2022)Examining Source Effects on Perceptions of Fake News in Rural IndiaProceedings of the ACM on Human-Computer Interaction10.1145/35129366:CSCW1(1-29)Online publication date: 7-Apr-2022
https://dl.acm.org/doi/10.1145/3512936
Toraman CŞahinuç FYilmaz EBaeza-Yates RWeller KPortela MSeneviratne OWeber IYasseri TBon ASrinivas SIbáñez L(2022)BlackLivesMatter 2020: An Analysis of Deleted and Suspended Users in TwitterProceedings of the 14th ACM Web Science Conference 202210.1145/3501247.3531539(290-295)Online publication date: 26-Jun-2022
https://dl.acm.org/doi/10.1145/3501247.3531539
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