@inproceedings{yang-etal-2019-tokyotech,
    title = "{T}okyo{T}ech{\_}{NLP} at {S}em{E}val-2019 Task 3: Emotion-related Symbols in Emotion Detection",
    author = "Yang, Zhishen  and
      Vijlbrief, Sam  and
      Okazaki, Naoaki",
    editor = "May, Jonathan  and
      Shutova, Ekaterina  and
      Herbelot, Aurelie  and
      Zhu, Xiaodan  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.",
    booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2019",
    address = "Minneapolis, Minnesota, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Ingest-2025-COMPUTEL/S19-2061/",
    doi = "10.18653/v1/S19-2061",
    pages = "350--354",
    abstract = "This paper presents our contextual emotion detection system in approaching the SemEval2019 shared task 3: EmoContext: Contextual Emotion Detection in Text. This system cooperates with an emotion detection neural network method (Poria et al., 2017), emoji2vec (Eisner et al., 2016) embedding, word2vec embedding (Mikolov et al., 2013), and our proposed emoticon and emoji preprocessing method. The experimental results demonstrate the usefulness of our emoticon and emoji prepossessing method, and representations of emoticons and emoji contribute model`s emotion detection."
}