Understanding engagement with U.S. (mis)information news sources on Facebook

  • Laura Edelson
  • , Minh Kha Nguyen
  • , Ian Goldstein
  • , Oana Goga
  • , Damon McCoy
  • , Tobias Lauinger

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Facebook has become an important platform for news publishers to promote their work and engage with their readers. Some news pages on Facebook have a reputation for consistently low factualness in their reporting, and there is concern that Facebook allows their misinformation to reach large audiences. To date, there is remarkably little empirical data about how often users "like," comment and share content from news pages on Facebook, how user engagement compares between sources that have a reputation for misinformation and those that do not, and how the political leaning of the source impacts the equation. In this work, we propose a methodology to generate a list of news publishers' official Facebook pages annotated with their partisanship and (mis)information status based on third-party evaluations, and collect engagement data for the 7.5 M posts that 2,551 U.S. news publishers made on their pages during the 2020 U.S. presidential election. We propose three metrics to study engagement (1) across the Facebook news ecosystem, (2) between (mis)information providers and their audiences, and (3) with individual pieces of content from (mis)information providers. Our results show that misinformation news sources receive widespread engagement on Facebook, accounting for 68.1% of all engagement with far-right news providers, followed by 37.7 % on the far left. Individual posts from misinformation news providers receive consistently higher median engagement than non-misinformation in every partisanship group. While most prevalent on the far right, misinformation appears to be an issue across the political spectrum.

Original languageEnglish
Title of host publicationIMC 2021 - Proceedings of the 2021 ACM Internet Measurement Conference
PublisherAssociation for Computing Machinery
Pages444-463
Number of pages20
ISBN (Electronic)9781450391290
DOIs
Publication statusPublished - 2 Nov 2021
Externally publishedYes
Event21st ACM Internet Measurement Conference, IMC 2021 - Virtual, Online, United States
Duration: 2 Nov 20214 Nov 2021

Publication series

NameProceedings of the ACM SIGCOMM Internet Measurement Conference, IMC

Conference

Conference21st ACM Internet Measurement Conference, IMC 2021
Country/TerritoryUnited States
CityVirtual, Online
Period2/11/214/11/21

Keywords

  • Facebook
  • engagement
  • measurement
  • misinformation
  • news

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