@inproceedings{dovdon-saias-2017-ej,
    title = "ej-sa-2017 at {S}em{E}val-2017 Task 4: Experiments for Target oriented Sentiment Analysis in {T}witter",
    author = "Dovdon, Enkhzol  and
      Saias, Jos{\'e}",
    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/iwcs-25-ingestion/S17-2106/",
    doi = "10.18653/v1/S17-2106",
    pages = "644--647",
    abstract = "This paper describes the system we have used for participating in Subtasks A (Message Polarity Classification) and B (Topic-Based Message Polarity Classification according to a two-point scale) of SemEval-2017 Task 4 Sentiment Analysis in Twitter. We used several features with a sentiment lexicon and NLP techniques, Maximum Entropy as a classifier for our system."
}