Abstract

The growing use of social media platforms offers a means to spread health-related information at an increased rate. However, disseminating health information on social media may be hazardous as the information often has no regulation. Therefore, it is crucial to find ways to classify health misinformation. Using machine learning models, this project utilizes mined Bangla text data and its English Translations to classify health misinformation from mined social media data. Multiple models were used such as Random Forest, XGBoost, SVC, etc, The highest reported precision in Bangla text and the English translation is 77 % and 79 % respectively. XGB classifier had the highest accuracy of 75% for English translation and the Extra Trees Classifier had the highest accuracy of 72 % for Bangla text.