Authors: Aryan Bhatt, Aryan Verma, Syed Qayam
Abstract: Social media has transformed the way people consume news by providing affordable, readily available, and quick information communication. Unfortunately, it has also provided a breeding ground for fake news—intentionally misleading or untruthful information—that can have serious consequences for individuals and society. Identification of fake news on social media has therefore become an essential research area. This problem differs from conventional news media, since false news is deliberately designed to mislead and thus cannot be easily detected by content alone. To overcome this, auxiliary data, including user behavior and social interactions, are usually needed. But it is hard to make use of this information because it is large-scale, incomplete, unstructured, and noisy. Considering the significance and complexity of the issue, the paper discusses Artificial Intelligence (AI) in the detection of false news on social media. We present an overview of the fake news features according to psychological theory and social theory, discuss previous AI-based detection algorithms, as well as assessment metrics and corpora. Further, we stress major challenges, current research work, and the possible future areas of AI use in detecting fake news.
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