Review of Machine Learning and Deep Learning based Methods for Phoney News Detection

• Published in: 2023 10th International Conference on Computing for Sustainable Global Development (INDIACom) pp. 1371 - 1377
• Main Authors: Sharma, Pushkar, Sahu, Rakesh
• Format: Conference Proceeding
• Language: English
• Published: Bharati Vidyapeeth, New Delhi 15.03.2023
• Subjects: Computer architecture; Convolutional neural networks; Deep learning; Machine Learning; Natural language processing; Neural Networks; Phoney News; Social networking (online); Support vector machines

Nowadays, getting news from online platforms, which include social media, news applications etc., is the most convenient and popular way, which is a positive. But this way has negatives also, in which the bigger challenge is phoney or misleading information which is spread by the users for their own benefit. Phoney news has the capability to eliminate peace in society and always create conflicts at a higher level. This influence of this type of content is the subject of research to remove it from the online platforms to maintain the trustworthiness of the online news. In this paper, we have summarized the work of 23 research papers. The techniques used in the papers are based on machine learning and deep learning. We have further concluded the overview of different methodologies and datasets used in these papers and their significance in future research to improve the existing architecture of classification of phoney news.