On estimating depressive tendencies of Twitter users utilizing their tweet data

In this paper, we investigate the effectiveness of the records of user´s activities in Twitter, which is a popular microblogging site, for estimating his/her depressive tendency. We construct multiple regression model to estimate user´s depressive tendency from the frequencies of words used by the user. We perform experiments to estimate participants´ depressive tendencies using the constructed regression model. Our experimental results show that there exists medium positive correlation (correlation coefficient r ≃ 0.45) between the Zung´s Self-rating Depression Scale, which is a popular measure for estimating depressive tendency, and estimated score obtained from the regression model.