Tracking Sentiment and Topic Dynamics from Social Media
Yulan He, Chenghua Lin, Wei Guang Gao, Kam‐Fai Wong · WORLD SCIENTIFIC eBooks · 2017
We propose a dynamic joint sentiment-topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are cap-tured by assuming that the current sentiment-topic spe-cific word distributions are generated according to the word distributions at previous epochs. We derive effi-cient online inference procedures to sequentially update the model with newly arrived data and show the effec-tiveness of our proposed model on the Mozilla add-on reviews crawled between 2007 and 2011.