@inproceedings{balazs-etal-2018-iiidyt,
    title = "{IIIDYT} at {IEST} 2018: Implicit Emotion Classification With Deep Contextualized Word Representations",
    author = "Balazs, Jorge  and
      Marrese-Taylor, Edison  and
      Matsuo, Yutaka",
    editor = "Balahur, Alexandra  and
      Mohammad, Saif M.  and
      Hoste, Veronique  and
      Klinger, Roman",
    booktitle = "Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis",
    month = oct,
    year = "2018",
    address = "Brussels, Belgium",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W18-6208/",
    doi = "10.18653/v1/W18-6208",
    pages = "50--56",
    abstract = "In this paper we describe our system designed for the WASSA 2018 Implicit Emotion Shared Task (IEST), which obtained 2nd place out of 30 teams with a test macro F1 score of 0.710. The system is composed of a single pre-trained ELMo layer for encoding words, a Bidirectional Long-Short Memory Network BiLSTM for enriching word representations with context, a max-pooling operation for creating sentence representations from them, and a Dense Layer for projecting the sentence representations into label space. Our official submission was obtained by ensembling 6 of these models initialized with different random seeds. The code for replicating this paper is available at \url{https://github.com/jabalazs/implicit_emotion}."
}