Multi-modal multi-layered topic classification model for social event analysis

Abstract

In this paper, we pay attention to reveal the event topics and track the evolutionary trend of social event and a novel probabilistic topic model is proposed. The Multi-modal Multi-layered Topic Classification Model (tm_MMC) for Social Event Analysis has the capacity for revealing visual and non-visual topics, by jointly modeling the textual and visual information while simultaneously learning and predicting the multi-layered category labels. In order to track the evolutionary trends of the topics online, tm_MMC uses topic intensity and heritability to incrementally build an up-to-date model. To evaluate the effectiveness of our model, we experiment using a collected data, and compare the results with those of other traditional models. The results demonstrate the effectiveness and advantages of our model against several state-of-the-art methods.