Tracking sentiment and topic dynamics from social media

Publication Type

Conference Proceeding Article

Publication Date

7-2012

Abstract

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 captured by assuming that the current sentiment-topic specific word distributions are generated according to the word distributions at previous epochs. We derive efficient online inference procedures to sequentially update the model with newly arrived data and show the effectiveness of our proposed model on the Mozilla add-on reviews crawled between 2007 and 2011.

Discipline

Databases and Information Systems

Research Areas

Data Science and Engineering

Publication

Proceedings of the 6th International AAAI Conference on Weblogs and Social Media (ICWSM 2012)

First Page

483

Last Page

486

Publisher

AAAI Press

City or Country

Dublin, Ireland

Additional URL

https://aaai.org/ICWSM/ICWSM12/paper/view/4496

This document is currently not available here.

Share

COinS