@inproceedings{lu-etal-2018-ecnu,
    title = "{ECNU} at {S}em{E}val-2018 Task 2: Leverage Traditional {NLP} Features and Neural Networks Methods to Address {T}witter Emoji Prediction Task",
    author = "Lu, Xingwu  and
      Mao, Xin  and
      Lan, Man  and
      Wu, Yuanbin",
    editor = "Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      May, Jonathan  and
      Shutova, Ekaterina  and
      Bethard, Steven  and
      Carpuat, Marine",
    booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/S18-1068/",
    doi = "10.18653/v1/S18-1068",
    pages = "433--437",
    abstract = "This paper describes our submissions to Task 2 in SemEval 2018, i.e., Multilingual Emoji Prediction. We first investigate several traditional Natural Language Processing (NLP) features, and then design several deep learning models. For subtask 1: Emoji Prediction in English, we combine two different methods to represent tweet, i.e., supervised model using traditional features and deep learning model. For subtask 2: Emoji Prediction in Spanish, we only use deep learning model."
}