@inproceedings{edouard-etal-2017-building,
    title = "Building timelines of soccer matches from {T}witter",
    author = "Edouard, Amosse  and
      Cabrio, Elena  and
      Tonelli, Sara  and
      Le-Thanh, Nhan",
    editor = "Mitkov, Ruslan  and
      Angelova, Galia",
    booktitle = "Proceedings of the International Conference Recent Advances in Natural Language Processing, {RANLP} 2017",
    month = sep,
    year = "2017",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd.",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/R17-1029/",
    doi = "10.26615/978-954-452-049-6_029",
    pages = "208--213",
    abstract = "This demo paper presents a system that builds a timeline with salient actions of a soccer game, based on the tweets posted by users. It combines information provided by external knowledge bases to enrich the content of tweets and applies graph theory to model relations between actions (e.g. goals, penalties) and participants of a game (e.g. players, teams). In the demo, a web application displays in nearly real-time the actions detected from tweets posted by users for a given match of Euro 2016. Our tools are freely available at \url{https://bitbucket.org/eamosse/event_tracking}."
}