@inproceedings{anderson-2019-sentim,
    title = "Sentim at {S}em{E}val-2019 Task 3: Convolutional Neural Networks For Sentiment in Conversations",
    author = "Anderson, Jacob",
    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/add-emnlp-2024-awards/S19-2052/",
    doi = "10.18653/v1/S19-2052",
    pages = "302--306",
    abstract = "In this work convolutional neural networks were used in order to determine the sentiment in a conversational setting. This paper`s contributions include a method for handling any sized input and a method for breaking down the conversation into separate parts for easier processing. Finally, clustering was shown to improve results and that such a model for handling sentiment in conversations is both fast and accurate."
}