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Publication Date: 30 Jan 2012
Type: Original Research
Journal: Biomedical Informatics Insights
Citation: Biomedical Informatics Insights 2012:5 (Suppl. 1) 195-204
doi: 10.4137/BII.S8958
In this paper we report on the approaches that we developed for the 2011 i2b2 Shared Task on Sentiment Analysis of Suicide Notes. We have cast the problem of detecting emotions in suicide notes as a supervised multi-label classification problem. Our classifiers use a variety of features based on (a) lexical indicators, (b) topic scores, and (c) similarity measures. Our best submission has a precision of 0.551, a recall of 0.485, and a F-measure of 0.516.
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