Abstract
Communication among people has been significantly enhanced by the recent advancements in social media. Social media platforms have enabled users to share information, connect with others, and stay informed about the latest events. However, social media can be a two-edged sword as it can be misused to spread unreliable information, such as fake news, which may be intended to deceive people, as witnessed in the 2016 U.S. presidential elections. Consequently, a considerable number of researchers are working towards identifying patterns and traits that fake news may exhibit to develop automated detection systems, given the gravity of this issue. However, fake news datasets have been created and made available to help devise such systems. In this study, we have described the FNC-1 dataset and given an overview of the competitive attempts to build a fake news detection system using the FNC-1 dataset. Besides, it highlights the strengths and weaknesses of each of these works.
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