Propagation from Deceptive News Sources: Who Shares, How Much, How Evenly, and How Quickly?
Maria Glenski, Tim Weninger, and Svitlana Volkova

TL;DR
This large-scale social media study analyzes how users share news from trusted and malicious sources, revealing key differences in propagation speed, distribution inequity, and demographic patterns across various types of misinformation on Twitter.
Contribution
It uniquely compares propagation behaviors across all news content types and demographics, highlighting disparities in spread and user engagement with different source trustworthiness.
Findings
Small group of users responsible for most disinformation spread
Users with lower income and education share more disinformation
Trusted sources propagate faster than suspicious ones
Abstract
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 eleven million posts and investigate 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 sub-population behaviour (by demographics) when spreading misinformation, and distinguish between 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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
