This paper describes the entry NUIG in the WASSA 20171 shared task on emotion recognition. The NUIG system used an SVR (SVM regression) and BiLSTM ensemble, utilizing primarily n-grams (for SVR features) and tweet word embeddings (for BiLSTM features). Experiments were carried out on several other candidate features, some of which were added to the SVR model. Parameter selection for the SVR model was run as a grid search whilst parameters for the BiLSTM model were selected through a non-exhaustive ad-hoc search.This work was supported in part by the European
Union supported project MixedEmotions (H2020-
644632) and the Science Foundation Ireland under
Grant Number SFI/12/RC/2289 (Insight)