Prediction of User Behaviour through the Interaction in Social Media Using Deep Learning Approach

Abstract

Predicting human behavior and personality from the social media applications like Facebook, Twitter and Instagram is achieving tremendous attention among researchers. Statistical information about the human thoughts expressed via status on social media is essential assets for research in predicting various human behaviour and personality. In addition to accurate prediction, having the capacity to understand the roles of human behavior determinants and to provide explanations for the predicted behaviors is also important. However, most prediction models do not provide explanations for the behaviors they predict. In this paper, user behaviour prediction is achieved using the Natural Language Processing (NLP) and Two-Level Classifier approach. User behaviour prediction on social media is usually defined as the problem of estimating the rating scores, view counts, or click through of a post. The proposed methodologies outperform compare with the existing approaches.