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        <title>UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets</title>
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            <namePart type="family">Apidianaki</namePart>
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            <namePart type="given">Saif</namePart>
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            <namePart type="given">Jonathan</namePart>
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    <abstract>This paper describes our system created for the SemEval-2018 Task 1: Affect in Tweets (AIT-2018). We participated in both the regression and the ordinal classification subtasks for emotion intensity detection in English, Arabic, and Spanish. For the regression subtask we use the AffectiveTweets system with added features using various word embeddings, lexicons, and LDA. For the ordinal classification we additionally use our Brainy system with features using parse tree, POS tags, and morphological features. The most beneficial features apart from word and character n-grams include word embeddings, POS count and morphological features.</abstract>
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%0 Conference Proceedings
%T UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets
%A Přibáň, Pavel
%A Hercig, Tomáš
%A Lenc, Ladislav
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Bethard, Steven
%Y Carpuat, Marine
%S Proceedings of the 12th International Workshop on Semantic Evaluation
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F priban-etal-2018-uwb
%X This paper describes our system created for the SemEval-2018 Task 1: Affect in Tweets (AIT-2018). We participated in both the regression and the ordinal classification subtasks for emotion intensity detection in English, Arabic, and Spanish. For the regression subtask we use the AffectiveTweets system with added features using various word embeddings, lexicons, and LDA. For the ordinal classification we additionally use our Brainy system with features using parse tree, POS tags, and morphological features. The most beneficial features apart from word and character n-grams include word embeddings, POS count and morphological features.
%R 10.18653/v1/S18-1018
%U https://aclanthology.org/S18-1018
%U https://doi.org/10.18653/v1/S18-1018
%P 133-140

Markdown (Informal)

[UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets](https://aclanthology.org/S18-1018) (Přibáň et al., SemEval 2018)

• UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets (Přibáň et al., SemEval 2018)

ACL

• Pavel Přibáň, Tomáš Hercig, and Ladislav Lenc. 2018. UWB at SemEval-2018 Task 1: Emotion Intensity Detection in Tweets. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 133–140, New Orleans, Louisiana. Association for Computational Linguistics.