EmotiKLUE at IEST 2018: Topic-Informed Classification of Implicit Emotions
2018-10-01WS 2018Code Available0· sign in to hype
Thomas Proisl, Philipp Heinrich, Besim Kabashi, Stefan Evert
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/tsproisl/EmotiKLUEOfficialIn papernone★ 0
Abstract
EmotiKLUE is a submission to the Implicit Emotion Shared Task. It is a deep learning system that combines independent representations of the left and right contexts of the emotion word with the topic distribution of an LDA topic model. EmotiKLUE achieves a macro average F₁score of 67.13\%, significantly outperforming the baseline produced by a simple ML classifier. Further enhancements after the evaluation period lead to an improved F₁score of 68.10\%.