Fake News Detection Using Decision Tree, Support Vector Machine And K-Nearest Neighbors Algorithms

Resumo

Fake news represents misinformation, typically spread across social networks, and possesses a significant potential for widespread dissemination online, which can lead to substantial societal issues. Therefore, it becomes imperative to explore and develop strategies aimed at minimizing such impacts, including the detection of fake news through the employment of machine learning (ML) techniques and algorithms. The purpose of this study is to examine the effectiveness and application of ML algorithms in identifying fake news. This research adopts an applied approach, focusing on a descriptive and quantitative analysis. The data for this study were sourced from the Kaggle platform, with data extraction conducted using Python, and analysis performed on the Jupyter Notebook platform.