THE ROLE OF SENTIMENT ANALYSIS AND DATA MINING SOLUTIONS IN THE STUDY OF FAKE NEWS AND COUNTERING DISINFORMATION

Abstract

The proposed article highlights the importance of studying the phenomenon of fake news spreading based on sentiment analysis solutions (use of natural language processing techniques) and data mining (obtaining relevant information from the study of data), given the diversification and travel speed of these types of news, as well as the need to implement mechanisms to assist us, in a first stage, in gaining a thorough understanding of them and, subsequently, in taking the necessary steps to limit the spread of the phenomenon. The method of qualitative analysis of specialised studies was used for this article.