A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities
December 02, 2018 ยท The Cartographer ยท ๐ arXiv.org
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"Title-pattern auto-detect: A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities"
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Authors
Xinyi Zhou, Reza Zafarani
arXiv ID
1812.00315
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.SI
Citations
307
Venue
arXiv.org
Last Checked
1 day ago
Abstract
The explosive growth in fake news and its erosion to democracy, justice, and public trust has increased the demand for fake news detection and intervention. This survey reviews and evaluates methods that can detect fake news from four perspectives: (1) the false knowledge it carries, (2) its writing style, (3) its propagation patterns, and (4) the credibility of its source. The survey also highlights some potential research tasks based on the review. In particular, we identify and detail related fundamental theories across various disciplines to encourage interdisciplinary research on fake news. We hope this survey can facilitate collaborative efforts among experts in computer and information sciences, social sciences, political science, and journalism to research fake news, where such efforts can lead to fake news detection that is not only efficient but more importantly, explainable.
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