This document summarizes research analyzing the sharing of links to "fake news" domains on Facebook from 2016 to 2021. The researchers collected data on over 40 million Facebook posts linking to over 1,500 questionable news domains. They analyzed the network of pages and groups sharing these links, finding clusters aligned with topics like progressives, conservatives, and conspiracy theories. They also analyzed how posts spread between pages, finding international communities focused on issues like climate change, vaccines, and politics. The research aims to understand the spread of problematic information on Facebook over time and across different communities.

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‘Fake News’ on Facebook:
A Longitudinal Analysis of
Link Sharing between 2016 and 2021
Edward Hurcombe, Axel Bruns, Daniel Angus, Stephen Harrington, and Jane Tan
e.hurcombe / a.bruns / daniel.angus / s.harrington / x28.tan @ qut.edu.au
QUT Digital Media Research Centre

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🚨 Work in Progress

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Aims
• Beyond ‘fake news’:
• Understanding the dissemination of problematic information across social media at scale
• Identifying different types of problematic information (by theme, audience, dynamics, …)
• Problematic information on Facebook:
• Dynamics of content sharing over time (key events, per domain, impact of take-downs)
• Networks of interaction and communities of interest (thematic, ideological, geographic, …)
• Funding:
• ARC Discovery project DP200101317:
Evaluating the Challenge of 'Fake News' and Other Malinformation

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Data
• FakeNIX:
• Iteratively updated masterlist of domains listed in existing studies of ‘fake news’
• 2,314 domains to date (from Shao et al., 2016; Starbird et al., 2017; Allcott et al., 2018;
Grinberg et al., 2019; Guess et al., 2018; 2019; etc.)
• Data from CrowdTangle: any Facebook posts from public pages / groups / verified profiles
that contained links to any of these domains during 1 Jan. 2016 to 31 Mar. 2021
• 🚨 Data gathering continues: dataset for ~1,500 domains to date (40.5m posts)
• Limitations:
• Public pages / groups / verified profiles (from here: spaces) only – no non-public sharing
• CrowdTangle coverage for spaces with small followings is incomplete / inconsistent
• ‘Fake news’ domain lists largely US- / Anglocentric

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Approach
• Network analysis:
• Link-sharing network:
• Bipartite network: space ↔ domain
• Structure expected to show clusters commonly sharing same domains
• Computational content analysis of posts per cluster
• Facebook on-sharing network:
• Public Facebook spaces sharing other spaces’ posts that contain FakeNIX links
• Monopartite network: public space ↔ public space
• Structure expected to show common interests, beliefs, politics

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Dynamics

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US
election
Inauguration
US
election
Capitol
riots
Inauguration
Pandemic
Impeachment

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Network Analysis

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Facebook spaces sharing
links to FakeNIX domains
Link-Sharing Network

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Space-Domain Network
Nodes: public pages, groups, verified profiles / domains in posts
Size: degree
Colour: degree
FakeNIX domain posts, 1 Jan. 2016 to 31 Mar. 2021 (incomplete)

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Space-Domain Network
Nodes: public pages, groups, verified profiles / domains in posts
Size: degree
Colour: degree
Major domains highlighted

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progressives
conservatives
French conspiracists LGBT
German
antivax
climate change
denial
Italian
Nigerian
end times
evangelist
pro-gun
military
Space-Domain Network
Nodes: public pages, groups, verified profiles / domains in posts
Size: degree
Colour: degree
Cluster identities interpreted from space and domain descriptions

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Space-Domain Network
Nodes: public pages, groups, verified profiles / domains in posts
Size: degree
Colour: network modularity detection
FakeNIX domain posts, 1 Jan. 2016 to 31 Mar. 2021 (incomplete)

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Space-Domain Network
Nodes: public pages, groups, verified profiles / domains in posts
Size: degree
Colour: network modularity detection
Key terms extracted from posts for major network clusters
progressives
conservatives
French conspiracists LGBT
German
antivax
climate change
denial
Italian
Nigerian
end times
evangelist
pro-gun
military

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Space-Domain Network
Nodes: public pages, groups, verified profiles / domains in posts
Size: degree
Colour: network modularity detection
Key terms extracted from posts for major network clusters
progressives
conservatives
French conspiracists LGBT
German
antivax
climate change
denial
Italian
Nigerian
end times
evangelist
pro-gun
military

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Facebook spaces sharing
other Facebook spaces’ posts
(that contain links to FakeNIX domains)
Facebook On-Sharing
Network

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US
election
Inauguration
US
election
Capitol
riots
Inauguration
Pandemic
Impeachment

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Space-Space Network
Nodes: public pages / groups / verified profiles
Size: in-degree
Colour: in-degree
Posts containing FakeNIX links shared from other Facebook spaces

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Space-Space Network
Nodes: public pages / groups / verified profiles
Size: in-degree
Colour: predominant location of admins (Facebook pages only)

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Page-Page Network
Nodes: public pages / groups / verified profiles
Size: in-degree
Colour: predominant location of admins (Facebook pages only)
Major shared spaces highlighted

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Italian
French
German
Brazilian
pro-Brexit
climate change
denial
antivax
conspiracists
progressives /
satire
alternative
nutrition
anti-Islam
end times
pro-Trump
conservatives
Ted Cruz
Nigerian
Malaysian
Slovakian
Polish
Chinese
anti-Brexit
finance
alternative
medicine
Romanian
Page-Page Network
Nodes: public pages / groups / verified profiles
Size: in-degree
Colour: predominant location of admins (Facebook pages only)
Cluster identities interpreted from space descriptions

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Summary

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Limitations and Outlook
• Limitations:
• public Facebook spaces only (pages, groups, and verified profiles)
• no data on non-public groups
• no data on public or non-public profile activity
• domain-level analysis only
• 🚨 data for 1,500 of 2,300 FakeNIX domains to date
• Outlook:
• general activity of most active FakeNIX sharers (including posts without FakeNIX links)
• further thematic analysis: which topics are prominent in which network contexts
• longitudinal analysis: changes over time (e.g. pre- / post-COVID)
• cross-platform analysis: comparisons with Twitter etc.

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This research is funded by the ARC project DP200101317 Evaluating the Challenge of 'Fake News'
and Other Malinformation.
It is also supported by the Australian Research Council Centre of Excellence for Automated Decision-
Making and Society.
Facebook data are provided courtesy of CrowdTangle.
Acknowledgments

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FakeNIX Sources
Allcott, H., Gentzkow, M., & Yu, C. (2018). Trends in the Diffusion of Misinformation on Social Media. https://arxiv.org/abs/1809.05901v1
Grinberg, N., Joseph, K., Friedland, L., Swire-Thompson, B., & Lazer, D. (2019). Fake News on Twitter during the 2016 U.S. Presidential Election. Science,
363(6425), 374–378. https://doi.org/10.1126/science.aau2706
Guess, A., Nyhan, B., & Reifler, J. (2018). Selective Exposure to Misinformation: Evidence from the Consumption of Fake News during the 2016 US Presidential
Campaign. Dartmouth College. http://www.dartmouth.edu/~nyhan/fake-news-2016.pdf
Guess, A., Nagler, J., & Tucker, J. (2019). Less than You Think: Prevalence and Predictors of Fake News Dissemination on Facebook. Science Advances, 5(1),
eaau4586. https://doi.org/10.1126/sciadv.aau4586
Shao, C., Ciampaglia, G. L., Flammini, A., & Menczer, F. (2016). Hoaxy: A Platform for Tracking Online Misinformation. Proceedings of the 25th International
Conference Companion on World Wide Web, 745–750. https://doi.org/10.1145/2872518.2890098
Starbird, K. (2017, March 15). Information Wars: A Window into the Alternative Media Ecosystem. Medium. https://medium.com/hci-design-at-uw/information-wars-a-
window-into-the-alternative-media-ecosystem-a1347f32fd8f