Abstract

Due to the complexity of emotions in suicide notes and the subtle nature of sentiments, this study proposes a fusion approach to tackle the challenge of sentiment classification in suicide notes: leveraging WordNet-based lexicons, manually created rules, character-based n-grams, and other linguistic features. Although our results are not satisfying, some valuable lessons are learned and promising future directions are identified.

Document Type

Article

Publication Date

1-30-2012

Notes/Citation Information

Published in Biomedical Infomatics Insights, v. 5, suppl. 1, p. 71-76.

© 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.

Digital Object Identifier (DOI)

http://dx.doi.org/10.4137/BII.S8949

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