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Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes

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....

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Detalles Bibliográficos
Autor principal: Pedersen, Ted
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Libertas Academica 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409475/
https://www.ncbi.nlm.nih.gov/pubmed/22879775
http://dx.doi.org/10.4137/BII.S8953
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author Pedersen, Ted
author_facet Pedersen, Ted
author_sort Pedersen, Ted
collection PubMed
description 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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spelling pubmed-34094752012-08-09 Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes Pedersen, Ted Biomed Inform Insights Original Research 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. Libertas Academica 2012-01-30 /pmc/articles/PMC3409475/ /pubmed/22879775 http://dx.doi.org/10.4137/BII.S8953 Text en © the author(s), publisher and licensee Libertas Academica Ltd. This is an open access article. Unrestricted non-commercial use is permitted provided the original work is properly cited.
spellingShingle Original Research
Pedersen, Ted
Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
title Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
title_full Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
title_fullStr Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
title_full_unstemmed Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
title_short Rule-Based and Lightly Supervised Methods to Predict Emotions in Suicide Notes
title_sort rule-based and lightly supervised methods to predict emotions in suicide notes
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3409475/
https://www.ncbi.nlm.nih.gov/pubmed/22879775
http://dx.doi.org/10.4137/BII.S8953
work_keys_str_mv AT pedersented rulebasedandlightlysupervisedmethodstopredictemotionsinsuicidenotes