Application of Machine Learning Techniques for Fake News Classification

ABSTRACT

Fake News consists of disseminating fake news in various social and digital media such as newspapers, television networks, and the internet. Fake news is not a new phenomenon in human behavior. However, the current dissemination is very different from what happened in the past. Social networks and the contemporary world have made it possible for the spread of lies to occur quickly and even intentionally. This causes serious problems, and its impacts can be felt in the real world. The identification of fake news can be useful in several contexts and can be used, for example, as a news filter in the virtual space. Thus, the present work aims to propose and evaluate strategies for processing and applying machine learning models, to improve the performance of classifiers in the problem of identifying fake news in Brazilian news.

KEYWORDS:

• Fake news
• machine learning
• Random Forest
• K-NN

Disclosure statement

No potential conflict of interest was reported by the author(s).