Abstract
Generating fake news has become a prevalent issue in the digital age, with profound consequences on society, politics, and media. Due to an exponential increase in the use of unverified information, spread on social media by users with different backgrounds, a significant task facing natural language processing is real-time recognition of generated fake news. The objective of this paper is to investigate the feasibility of utilizing artificial intelligence (AI) for the automatic generation of fake news that possesses a sufficiently high level of quality to serve as a synthetic corpus. These automatically generated texts are subsequently used to improve fake news detectors, evaluated on different publicly available datasets fake news datasets, but also against a novel fake news corpus, especially developed for this research.
Published Version
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