Propagation From Deceptive News Sources Who Shares, How Much, How Evenly, and How Quickly?

Journal Article · Wed Nov 21 00:00:00 EST 2018 · IEEE Transactions on Computational Social Systems

DOI:https://doi.org/10.1109/TCSS.2018.2881071· OSTI ID:1483420

Glenski, Maria ^[1]; Weninger, Tim ^[1]; Volkova, Svitlana ^[2]

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1. Univ. of Notre Dame, Notre Dame, IN (United States)
2. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

As people rely on social media as their primary sources of news, the spread of misinformation has become a significant concern. In this large-scale study of news in social media, we analyze 11 million posts and investigate the propagation behavior of users that directly interact with news accounts identified as spreading trusted versus malicious content. Unlike previous work, which looks at specific rumors, topics, or events, we consider all content propagated by various news sources. Moreover, we analyze and contrast population versus subpopulation behavior (by demographics) when spreading misinformation, and distinguish between the two types of propagation, i.e., direct retweets and mentions. Our evaluation examines how evenly, how many, how quickly, and which users propagate content from various types of news sources on Twitter. Our analysis has identified several key differences in propagation behavior from trusted versus suspicious news sources. These include high inequity in the diffusion rate based on the source of disinformation, with a small group of highly active users responsible for the majority of disinformation spread overall and within each demographic. Analysis by demographics showed that users with lower annual income and education share more from disinformation sources compared to their counterparts. News content is shared significantly more quickly from trusted, conspiracy, and disinformation sources compared to clickbait and propaganda. Older users propagate news from trusted sources more quickly than younger users, but they share from suspicious sources after longer delays. Lastly, users who interact with clickbait and conspiracy sources are likely to share from propaganda accounts, but not the other way around.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• Grant/Contract Number: AC05-76RL01830
• OSTI ID: 1483420
• Alternate ID(s): OSTI ID: 1529941
• Journal Information: IEEE Transactions on Computational Social Systems, Journal Name: IEEE Transactions on Computational Social Systems Journal Issue: 4 Vol. 5; ISSN 2373-7476
• Publisher: IEEE
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
deception
disinformation
information propagation
misinformation
social network analysis