EmotiKLUE at IEST 2018: Topic-Informed Classification of Implicit Emotions - Proisl, Thomas; Heinrich, Philipp; Kabashi, Besim; Evert, Stephanie (Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 2018)
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 F 1 score of 67.13%, significantly outperforming the baseline produced by a simple ML classifier. Further enhancements after the evaluation period lead to an improved F 1 score of 68.10%<br