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    <abstract>This paper describes the entry NUIG in the WASSA 2017 (8th Workshop on Computational Approaches to Subjectivity, Sentiment &amp; Social Media Analysis) shared task on emotion recognition. The NUIG system used an SVR (SVM regression) and BLSTM ensemble, utilizing primarily n-grams (for SVR features) and tweet word embeddings (for BLSTM 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 BLSTM model were selected through a non-exhaustive ad-hoc search.</abstract>
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%0 Conference Proceedings
%T NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity
%A Andryushechkin, Vladimir
%A Wood, Ian
%A O’ Neill, James
%Y Balahur, Alexandra
%Y Mohammad, Saif M.
%Y van der Goot, Erik
%S Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F andryushechkin-etal-2017-nuig
%X This paper describes the entry NUIG in the WASSA 2017 (8th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis) shared task on emotion recognition. The NUIG system used an SVR (SVM regression) and BLSTM ensemble, utilizing primarily n-grams (for SVR features) and tweet word embeddings (for BLSTM 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 BLSTM model were selected through a non-exhaustive ad-hoc search.
%R 10.18653/v1/W17-5223
%U https://aclanthology.org/W17-5223
%U https://doi.org/10.18653/v1/W17-5223
%P 175-179

Markdown (Informal)

[NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity](https://aclanthology.org/W17-5223) (Andryushechkin et al., WASSA 2017)

• NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity (Andryushechkin et al., WASSA 2017)

ACL

• Vladimir Andryushechkin, Ian Wood, and James O’ Neill. 2017. NUIG at EmoInt-2017: BiLSTM and SVR Ensemble to Detect Emotion Intensity. In Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 175–179, Copenhagen, Denmark. Association for Computational Linguistics.