@inproceedings{muller-etal-2017-topicthunder,
    title = "{T}opic{T}hunder at {S}em{E}val-2017 Task 4: Sentiment Classification Using a Convolutional Neural Network with Distant Supervision",
    author = {M{\"u}ller, Simon  and
      Huonder, Tobias  and
      Deriu, Jan  and
      Cieliebak, Mark},
    editor = "Bethard, Steven  and
      Carpuat, Marine  and
      Apidianaki, Marianna  and
      Mohammad, Saif M.  and
      Cer, Daniel  and
      Jurgens, David",
    booktitle = "Proceedings of the 11th International Workshop on Semantic Evaluation ({S}em{E}val-2017)",
    month = aug,
    year = "2017",
    address = "Vancouver, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/S17-2129/",
    doi = "10.18653/v1/S17-2129",
    pages = "766--770",
    abstract = "In this paper, we propose a classifier for predicting topic-specific sentiments of English Twitter messages. Our method is based on a 2-layer CNN.With a distant supervised phase we leverage a large amount of weakly-labelled training data. Our system was evaluated on the data provided by the SemEval-2017 competition in the Topic-Based Message Polarity Classification subtask, where it ranked 4th place."
}