[2006.05489v2] Modeling Label Semantics for Predicting Emotional Reactions
[2006.05489v2] Modeling Label Semantics for Predicting Emotional Reactions Computer Science > Computation and Language arXiv:2006.05489v2 (cs) [Submitted on 9 Jun 2020 ( v1 ), last revised 28 Jun 2020 (this version, v2)] Title: Modeling Label Semantics for Predicting Emotional Reactions Authors: Radhika Gaonkar , Heeyoung Kwon , Mohaddeseh Bastan , Niranjan Balasubramanian , Nathanael Chambers View a PDF of the paper titled Modeling Label Semantics for Predicting Emotional Reactions, by Radhika Gaonkar and 4 other authors View PDF Abstract: Predicting how events induce emotions in the characters of a story is typically seen as a standard multi-label classification task, which usually treats labels as anonymous classes to predict. They ignore information that may be conveyed by the emotion labels themselves.
Abstract page for arXiv paper 2006.05489v2: Modeling Label Semantics for Predicting Emotional Reactions