AAAI Publications, Workshops at the Twenty-Seventh AAAI Conference on Artificial Intelligence

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What Affects Patient (Dis)satisfaction? Analyzing Online Doctor Ratings with a Joint Topic-Sentiment Model
Michael J. Paul, Byron C. Wallace, Mark Dredze

Last modified: 2013-06-29


We analyze patient reviews of doctors using a novel probabilistic joint model of topic and sentiment based on factorial LDA (Paul and Dredze 2012). We leverage this model to exploit a small set of previously annotated reviews to automatically analyze the topics and sentiment latent in over 50,000 online reviews of physicians (and we make this dataset publicly available). The proposed model outperforms baseline models for this task with respect to model perplexity and sentiment classification. We report the most representative words with respect to positive and negative sentiment along three clinical aspects, thus complementing existing qualitative work exploring patient reviews of physicians.


topic modeling; sentiment analysis; doctor reviews

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