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Fake News Detection and Analysis
- 1 University of Melbourne
- 2 Shihezi University
- 3 Chongqing University
- 4 University of Southern California
* Author to whom correspondence should be addressed.
Abstract
The popularized use of social media accelerates the spreading of fake news. The overwhelming amount of fake news was a severe social issue during the 2016 presidential election and the first outbreak of Coronavirus in 2020. As controlling the spread of fake news is not practically workable, the detection of fake news is significantly valuable to solve this issue. In this paper, we conduct experiments to discover the effect of contextualized embedding of news content on counterfeit news detection. We also explore the features of fake news through two aspects: clickbait and sentiment.
Keywords
fake news detection, deep learning, contextualized embedding
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Cite this article
Zhang,B.;Dai,C.;Deng,Z.;Jiang,Z. (2023). Fake News Detection and Analysis. Communications in Humanities Research,7,22-30.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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