Monitoring human health condition on OSN Overtime

Abstract

Social media has become a major source for analyzing all as-pects of daily life. Thanks to dedicated latent topic analysis methods such as the Ailment Topic Aspect Model (ATAM), public health can now be observed on Twitter. In this work, we are interested in monitoring people’s health over time. Recently, Temporal-LDA (TM–LDA) was proposed for effi-ciently modeling general-purpose topic transitions over time.