TY  - JOUR
PY  - 2012//
TI  - Statistical and similarity methods for classifying emotion in suicide notes
JO  - Biomedical informatics insights
A1  - Roberts, Kirk
A1  - Harabagiu, Sanda M.
SP  - 195
EP  - 204
VL  - 5
IS  - Suppl 1
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 1178-2226
UR  - http://dx.doi.org/10.4137/BII.S8958
ID  - ref1
ER  -