Open AccessAi4Truth: An In-depth Analysis on Misinformation using Machine Learning and Data Science
Author(s) -
Kevin Qu,
Sun Yu
Publication year - 2021
Publication title -
natural language processing
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5121/csit.2021.112327
Subject(s) - misinformation , computer science , process (computing) , fake news , social media , data science , artificial intelligence , machine learning , information retrieval , internet privacy , world wide web , computer security , operating system
A number of social issues have been grown due to the increasing amount of “fake news”. With the inevitable exposure to this misinformation, it has become a real challenge for the public to process the correct truth and knowledge with accuracy. In this paper, we have applied machine learning to investigate the correlations between the information and the way people treat it. With enough data, we are able to safely and accurately predict which groups are most vulnerable to misinformation. In addition, we realized that the structure of the survey itself could help with future studies, and the method by which the news articles are presented, and the news articles itself also contributes to the result.