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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
1-1-2012
Digital Object Identifier (DOI)
https://doi.org/10.4137/BII.S8949
Repository Citation
Yu, Ning; Kübler, Sandra; Herring, Joshua; Hsu, Yu-Yin; Israel, Ross; and Smiley, Charese, "LASSA: Emotion Detection via Information Fusion" (2012). Information Science Faculty Publications. 14.
https://uknowledge.uky.edu/slis_facpub/14
Notes/Citation Information
Published in Biomedical Infomatics Insights, v. 5, suppl. 1, p. 71-76.
© the author(s), publisher and licensee Libertas Academica Ltd.
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