@inproceedings{park-etal-2018-plusemo2vec,
    title = "{P}lus{E}mo2{V}ec at {S}em{E}val-2018 Task 1: Exploiting emotion knowledge from emoji and {\#}hashtags",
    author = "Park, Ji Ho  and
      Xu, Peng  and
      Fung, Pascale",
    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/jlcl-multiple-ingestion/S18-1039/",
    doi = "10.18653/v1/S18-1039",
    pages = "264--272",
    abstract = "This paper describes our system that has been submitted to SemEval-2018 Task 1: Affect in Tweets (AIT) to solve five subtasks. We focus on modeling both sentence and word level representations of emotion inside texts through large distantly labeled corpora with emojis and hashtags. We transfer the emotional knowledge by exploiting neural network models as feature extractors and use these representations for traditional machine learning models such as support vector regression (SVR) and logistic regression to solve the competition tasks. Our system is placed among the Top3 for all subtasks we participated."
}