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Tracking sentiment and topic dynamics from social media

Country : Singapore
Department : Singapore Management University
Project Title : Tracking sentiment and topic dynamics from social media
Researcher : HE, Yulan , LIN, Chenghua , GAO, Wei , WONG, Kam-Fai
Keyword : Databases and Information Systems
Publisher : Institutional Knowledge at Singapore Management University
Year End : 2012
Identifier : https://ink.library.smu.edu.sg/sis_research/4611
Source : Research Collection School Of Information Systems
Abstract / Description :

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.

References

HE, Yulan and others / et al. (2012). Tracking sentiment and topic dynamics from social media.  Singapore: Singapore Management University.
HE, Yulan and others / et al. 2012. "Tracking sentiment and topic dynamics from social media".  Singapore: Singapore Management University.
HE, Yulan and others / et al. "Tracking sentiment and topic dynamics from social media."  Singapore: Singapore Management University, 2012. Print.
HE, Yulan and others / et al. Tracking sentiment and topic dynamics from social media. Singapore: Singapore Management University; 2012.

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