Understanding User Profiles on Social Media for Fake News Detection

By Kai Shu, Suhang Wang, Huan Liu. Conference on Multimedia Information Processing and Retrieval, 2018

302 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/1737253c3c1cd4466d195e421fc6d5af10096ad0

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In Information Systems

In Sociology and Political Science

Citations in the corpus

Beyond News Contents: The Role of Social Context for Fake News Detection (2017, methodology): “For example, Shu et al. [34] proposed to understand user profiles from various aspects to differentiate fake news.”
FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media (2018, unknown): “User Proﬁles User proﬁles on social media have been shown to be correlated with fake news detection (Shu, Wang, and Liu 2018).”
FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media (2018, background): “For example, study has shown that the clickbaits headlines usually can serve as a good indicator for recognizing fake news articles (Chen, Conroy, and Rubin 2015; Shu et al. 2018).”
Fake News Detection on Social Media using Geometric Deep Learning (2019, background): “Social context features include user demographics (such as age, gender, education, and political affiliation [37, 21]), social network structure [38, 35] (in the form of connections between users such as friendship or follower/followee relations) and user reactions (e.”
Mining Dual Emotion for Fake News Detection (2019, background): “To tackle this issue, researchers have been devoted to developing automatic methods to detect fake news (i.e., designing a classifier to judge a given news piece as real or fake) by leveraging signals from text [5, 32, 34], images [20, 35], or social contexts [17, 24, 26– 28, 39, 40].”
Fake news, disinformation and misinformation in social media: a review (2023, unknown): “Several authors (Shu et al. 2018b, 2017; Shi et al. 2019; Bessi and Ferrara 2016; Shao et al. 2018a) have also shown that fake news is likely to be created and spread by non-human accounts with similar attributes and structure in the network, such as social bots (Ferrara et al. 2016).”