Fake or fact? Evaluating chatbots’ performance to help users detect fake news in human-computer communities

Bibliographic Data

ID21719087
AuthorsZehang Xie (0000-0003-2665-2640, Shanghai Jiao Tong University), Hui Hui (0000-0002-6732-4232, Shanghai Jiao Tong University), Yunxiang Xie (0009-0006-5268-3693, Quanzhou Vocational and Technical University, corresponding author)
Year2025
Publication date2025-11-06
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueJournalism (JOURNAL)
Journal identifiersISSN: 1464-8849 • E-ISSN: 1741-3001
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/14648849251395797
OpenAlexW4415967273
LanguageEN
Citations received1
References cited47

The rapid proliferation of fake news poses a significant challenge to information ecosystems, particularly in digital and social media environments. This study investigates the effectiveness of chatbot interventions in assisting users with fake news detection within human-computer communities. Grounded in the Heuristic-Systematic Model, the study employs a 6 (fake news type) × 3 (chatbot intervention strategy) mixed design to examine how different chatbot strategies - fact-checking, contextual explanations, and authority endorsements - affect users’ ability to identify various types of fake news. The results show that fact-checking is most effective for detecting fabrication and photo manipulation, contextual explanations enhance recognition of satire and parody-based fake news, and authority endorsements are particularly useful in countering propaganda. These findings highlight the importance of tailoring chatbot interventions to specific fake news types

Chatbot · Fake news · Psychological intervention · Social media · AI in Service Interactions · Misinformation and Its Impacts · Spam and Phishing Detection