@inproceedings{andy-etal-2019-winter,
    title = "Winter is here: Summarizing {T}witter Streams related to Pre-Scheduled Events",
    author = "Andy, Anietie  and
      Wijaya, Derry Tanti  and
      Callison-Burch, Chris",
    editor = "Ferraro, Francis  and
      Huang, Ting-Hao {`}Kenneth{'}  and
      Lukin, Stephanie M.  and
      Mitchell, Margaret",
    booktitle = "Proceedings of the Second Workshop on Storytelling",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/W19-3412/",
    doi = "10.18653/v1/W19-3412",
    pages = "112--116",
    abstract = "Pre-scheduled events, such as TV shows and sports games, usually garner considerable attention from the public. Twitter captures large volumes of discussions and messages related to these events, in real-time. Twitter streams related to pre-scheduled events are characterized by the following: (1) spikes in the volume of published tweets reflect the highlights of the event and (2) some of the published tweets make reference to the characters involved in the event, in the context in which they are currently portrayed in a subevent. In this paper, we take advantage of these characteristics to identify the highlights of pre-scheduled events from tweet streams and we demonstrate a method to summarize these highlights. We evaluate our algorithm on tweets collected around 2 episodes of a popular TV show, Game of Thrones, Season 7."
}