Personalized Mood Prediction Over Online Social Networks: Data Analysis on Cyber-Social-Physical Dimensions

We built a personalized system that can predict the upcoming user mood even in days without text-type tweets. We, first, study the correlation of three types of features (cyber, social and physical) with a user mood. Then, we use these features to train a predictive system. The results suggest a statistically significant correlation between user mood and his cyber, social and physical activities distributed among different OSNs, which lead to a low RMSE in our predictive system compared to linguistic-based systems when non-text content is available.