Rumor Stance Prediction

Now a days false claims and rumors are been spreading very widely through the social media which may affect people perspective and may also lead some harm. This rumors are mainly growing faster through the twitter platform which is essential to classify or detect the posted news is a true incident or just a rumor. In our proposed model we are using Machine learning and deep learning techniques to classify the posted news was a rumor or not. Here, we are using Naive Bayes, Support Vector Machine (SVM) and Logistic Regression models from the machine learning and Neural Network from the deep learning. The classification is performed on the stance that was possessed by the tweet. Those stance are divided into four categories, named as supporting, deny, query and commenting. We will use this categories for our classification using the mentioned machine and deep learning techniques and predict the accuracies of each model we are using. At final, we are comparing the accuracies of each model we are using that which can be used further for the detection of the rumor.

Keywords: Rumor Classification, Supporting, Deny, Query, Commenting, Machine Learning, Deep Learning, Naive Bayes, Support Vector Machine (SVM), Logistic Regression, Neural Network.