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Full-Text Articles in Social and Behavioral Sciences
Discerning Emotions In Texts, Victoria L. Rubin, Jeffrey M. Stanton, Elizabeth D. Liddy
Discerning Emotions In Texts, Victoria L. Rubin, Jeffrey M. Stanton, Elizabeth D. Liddy
School of Information Studies - Faculty Scholarship
We present an empirically verified model of discernable emotions, Watson and Tellegen’s Circumplex Theory of Affect from social and personality psychology, and suggest its usefulness in NLP as a potential model for an automation of an eight-fold categorization of emotions in written English texts. We developed a data collection tool based on the model, collected 287 responses from 110 non-expert informants based on 50 emotional excerpts (min=12, max=348, average=86 words), and analyzed the inter-coder agreement per category and per strength of ratings per sub-category. The respondents achieved an average 70.7% agreement in the most commonly identified emotion categories per text. …