Citation

Yu N, Kübler S, Herring J, Hsu YY, Israel R, Smiley C. Biomed. Inform. Insights 2012; 5(Suppl 1): 71-76.

Affiliation

Assistant Professor, University of Kentucky, Lexington, KY, USA.

Copyright

(Copyright © 2012, Libertas Academica)

DOI

10.4137/BII.S8949

PMID

22879762

PMCID

PMC3409490

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.

Language: en