Tübingen-Oslo at SemEval-2018 Task 2: SVMs perform better than RNNs in Emoji Prediction.

Çagri Çöltekin, Taraka Rama

Abstract: This paper describes our participation in the SemEval-2018 task Multilingual Emoji Prediction. We participated in both English and Spanish subtasks, experimenting with support vector machines (SVMs) and recurrent neural networks. Our SVM classifier obtained the top rank in both subtasks with macro-averaged F1-measures of 35.99% for English and 22.36% for Spanish data sets. Similar to a few earlier attempts, the results with neural networks were not on par with linear SVMs.