Kuijper, Marloes

van Lenthe, Mike

van Noord, Rik

English

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

Proceedings - University of Groningen

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

https://pure.rug.nl/ws/files/78994480/S18_1041.pdf

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

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Proceedings - University of Groningen