Human Mobility Prediction Through Twitter

Abstract

Social media, in recent years, have become an invaluable source of information concerning human dynamics within urban context, allowing to enhance the comprehension of people behaviour, including human mobility regularities. The paper presents an approach to predict human mobility by exploiting Twitter data. The prediction approach is based on a novel trajectory pattern similarity measure that allows to identify the more suitable historic patterns to exploit for the prediction of the user next location. The pattern with the highest similarity to the user current trajectory will be used to predict the user next position. The experimental results obtained by using a real-world dataset show that the proposed method is effective in predicting the users next places achieving a remarkable precision.