Rule-based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
Author(s) -
Ted Pedersen
Publication year - 2012
Publication title -
biomedical informatics insights
Language(s) - English
Resource type - Journals
ISSN - 1178-2226
DOI - 10.4137/bii.s8953
Subject(s) - measure (data warehouse) , bigram , computer science , psychology , artificial intelligence , natural language processing , statistics , data mining , mathematics , trigram
This paper describes the Duluth systems that participated in the Sentiment Analysis track of the i2b2/VA/Cincinnati Children's 2011 Challenge. The top Duluth system was a rule-based approach derived through manual corpus analysis and the use of measures of association to identify significant ngrams. This performed in the median range of systems, attaining an F-measure of 0.45. The second system was automatically derived from the most frequent bigrams unique to one or two emotions. It achieved an F-measure of 0.36. The third system was the union of the first two, and reached an F-measure of 0.44.
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