UG18 at SemEval-2018 Task 1: Generating Additional Training Data for Predicting Emotion Intensity in Spanish

Kuijper, M., van Lenthe, M. & van Noord, R., 5-Jun-2018, Proceedings of The 12th International Workshop on Semantic Evaluation. Apidianaki, M., Mohammad, S. M., May, J., Shutova, E., Bethard, S. & Carpuat, M. (eds.). New Orleans, Louisiana : Association for Computational Linguistics (ACL), p. 279-285 7 p.

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The present study describes our submission to SemEval 2018 Task 1: Affect in Tweets. Our Spanish-only approach aimed to demonstrate that it is beneficial to automatically generate additional training data by (i) translating training data from other languages and (ii) applying a semi-supervised learning method. We find strong support for both approaches, with those models outperforming our regular models in all subtasks. However, creating a stepwise ensemble of different models as opposed to simply averaging did not result in an increase in performance. We placed second (EI-Reg), second (EI-Oc), fourth (V-Reg) and fifth (V-Oc) in the four Spanish subtasks we participated in.
Original languageEnglish
Title of host publicationProceedings of The 12th International Workshop on Semantic Evaluation
EditorsMarianna Apidianaki, Saif M. Mohammad, Jonathan May , Ekaterina Shutova, Steven Bethard, Marine Carpuat
Place of PublicationNew Orleans, Louisiana
PublisherAssociation for Computational Linguistics (ACL)
Number of pages7
Publication statusPublished - 5-Jun-2018


  • Sentiment analysis, Emotion intensity, Neural Networks, Semi-supervised learning

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