Abstract
This work studies sentiment and factual transitions on an online medical forum where users correspond in English. We work with discussions dedicated to reproductive technologies, an emotionally-charged issue. In several learning problems, we demonstrate that multi-class sentiment classification significantly improves when messages are represented by affective terms combined with sentiment and factual transition information (paired t-test, P=0.0011).Publisher
SpringerJournal
Advances in Artificial Intelligence, 28th Canadian Conference on Artificial IntelligenceType
Journal articleLanguage
enISBN
978-3-319-18356-5Sponsors
Self-fundedCollections
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