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Community-based fact-checking is a promising approach to verify social media content and correct misleading posts at scale. Yet, causal evidence regarding its effectiveness in reducing the spread of misinformation on social media is…

Social and Information Networks · Computer Science 2024-09-16 Yuwei Chuai , Moritz Pilarski , Thomas Renault , David Restrepo-Amariles , Aurore Troussel-Clément , Gabriele Lenzini , Nicolas Pröllochs

Social networks scaffold the diffusion of information on social media. Much attention has been given to the spread of true vs. false content on online social platforms, including the structural differences between their diffusion patterns.…

Social and Information Networks · Computer Science 2026-03-24 Isaac Slaughter , Axel Peytavin , Johan Ugander , Martin Saveski

Misinformation undermines the credibility of social media and poses significant threats to modern societies. As a countermeasure, Twitter has recently introduced "Birdwatch," a community-driven approach to address misinformation on Twitter.…

Social and Information Networks · Computer Science 2021-12-15 Nicolas Pröllochs

Developing interventions that successfully reduce engagement with misinformation on social media is challenging. One intervention that has recently gained great attention is X/Twitter's Community Notes (previously known as "Birdwatch").…

Social and Information Networks · Computer Science 2024-08-26 Yuwei Chuai , Haoye Tian , Nicolas Pröllochs , Gabriele Lenzini

In recent years, the proliferation of misinformation on social media platforms has become a significant concern. Initially designed for sharing information and fostering social connections, platforms like Twitter (now rebranded as X) have…

Computers and Society · Computer Science 2026-01-28 Uku Kangur , Roshni Chakraborty , Rajesh Sharma

Two commonly employed strategies to combat the rise of misinformation on social media are (i) fact-checking by professional organisations and (ii) community moderation by platform users. Policy changes by Twitter/X and, more recently, Meta,…

Computation and Language · Computer Science 2025-05-28 Nadav Borenstein , Greta Warren , Desmond Elliott , Isabelle Augenstein

The spread of misinformation on social media is a pressing societal problem that platforms, policymakers, and researchers continue to grapple with. As a countermeasure, recent works have proposed to employ non-expert fact-checkers in the…

Social and Information Networks · Computer Science 2023-03-28 Chiara Drolsbach , Nicolas Pröllochs

Community-based fact-checking systems, such as Community Notes on X (formerly Twitter), aim to mitigate online misinformation by surfacing annotations judged helpful by contributors with diverse viewpoints. While prior work has shown that…

Social and Information Networks · Computer Science 2026-01-21 Yuwei Chuai , Gabriele Lenzini , Nicolas Pröllochs

Deploying links to fact-checking websites (so-called "snoping") is a common intervention that can be used by social media users to refute misleading claims. However, its real-world effect may be limited as it suffers from low visibility and…

Social and Information Networks · Computer Science 2023-09-19 Moritz Pilarski , Kirill Solovev , Nicolas Pröllochs

Crowdsourced moderation systems like Twitter/X's Community Notes program have been proposed as scalable alternatives to professional fact-checkers for combating online misinformation. While prior research has examined the effectiveness of…

Human-Computer Interaction · Computer Science 2026-03-13 Morgan Wack , Patrick Warren , Mustafa Alam

The prevalence of social media has made information sharing possible across the globe. The downside, unfortunately, is the wide spread of misinformation. Methods applied in most previous rumor classifiers give an equal weight, or attention,…

Social and Information Networks · Computer Science 2019-10-04 Sansiri Tarnpradab , Kien A. Hua

Social networks offer a ready channel for fake and misleading news to spread and exert influence. This paper examines the performance of different reputation algorithms when applied to a large and statistically significant portion of the…

Social and Information Networks · Computer Science 2019-02-20 Rakshit Agrawal , Luca de Alfaro , Gabriele Ballarin , Stefano Moret , Massimo Di Pierro , Eugenio Tacchini , Marco L. Della Vedova

The link between affect, defined as the capacity for sentimental arousal on the part of a message, and virality, defined as the probability that it be sent along, is of significant theoretical and practical importance, e.g. for viral…

Social and Information Networks · Computer Science 2015-03-17 Lars Kai Hansen , Adam Arvidsson , Finn Årup Nielsen , Elanor Colleoni , Michael Etter

Major social media platforms increasingly adopt community-based fact-checking to address misinformation on their platforms. While previous research has largely focused on its effect on engagement (e.g., reposts, likes), an understanding of…

Social and Information Networks · Computer Science 2025-05-16 Michelle Bobek , Nicolas Pröllochs

Displaying community fact-checks is a promising approach to reduce engagement with misinformation on social media. However, how users respond to misleading content emotionally after community fact-checks are displayed on posts is unclear.…

Social and Information Networks · Computer Science 2025-01-28 Yuwei Chuai , Anastasia Sergeeva , Gabriele Lenzini , Nicolas Pröllochs

Online misinformation has been a serious threat to public health and society. Social media users are known to reply to misinformation posts with counter-misinformation messages, which have been shown to be effective in curbing the spread of…

Social and Information Networks · Computer Science 2023-03-17 Yingchen Ma , Bing He , Nathan Subrahmanian , Srijan Kumar

Fact-checking ecosystems on social media depend on the interplay between what users want checked and what contributors are willing to supply. Prior research has largely examined these forces in isolation, yet it remains unclear to what…

Social and Information Networks · Computer Science 2026-02-06 Moritz Pilarski , Nicolas Pröllochs

During sudden onset crisis events, the presence of spam, rumors and fake content on Twitter reduces the value of information contained on its messages (or "tweets"). A possible solution to this problem is to use machine learning to…

Cryptography and Security · Computer Science 2015-02-02 Aditi Gupta , Ponnurangam Kumaraguru , Carlos Castillo , Patrick Meier

Community-based fact-checking is a promising approach to address misinformation on social media at scale. However, an understanding of what makes community-created fact-checks helpful to users is still in its infancy. In this paper, we…

Social and Information Networks · Computer Science 2025-03-14 Kirill Solovev , Nicolas Pröllochs

Social media posts may go viral and reach large numbers of people within a short period of time. Such posts may threaten the public dialogue if they contain misleading content, making their early detection highly crucial. Previous works…

Social and Information Networks · Computer Science 2023-03-14 Tuğrulcan Elmas , Stephane Selim , Célia Houssiaux
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