Fake News Detection system using Decision Tree algorithm and compare textual property with Support Vector Machine algorithm

Abstract

To find out precise Fake News Detection on social media, the Decision Tree (DT) machine learning algorithm has to be worked out and also compare textual property accuracy with Support Vector Machine (SVM) machine learning algorithm. Materials and Methods: The analysis was done for fake news detection using machine learning algorithms such as the DT algorithm (N=311) and SVM algorithm (N=311) as a proposed research. Results: The DT algorithm and SVM algorithm’s accuracy for social media fake news were experimented and measured. The DT machine algorithm accuracy measures appears to be 97.67% and it is better than the SVM algorithm accuracy and it appears to be 91.74%. There is a statistically significant difference among the study groups with significance value 0.092 for accuracy and 0.825 for precision for Confidence Interval (CI) 95%. Conclusion: The DT machine algorithm is used in examining whether a piece of news from social media is fake or not with accuracy that appears to be better than the SVM algorithm machine learning algorithm.