Building timelines of soccer matches from Twitter

Amosse Edouard, Elena Cabrio, Sara Tonelli, Nhan Le-Thanh


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 https://bitbucket.org/eamosse/event_tracking.
Anthology ID:
R17-1029
Volume:
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2017
Month:
September
Year:
2017
Address:
Varna, Bulgaria
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
208–213
Language:
URL:
https://doi.org/10.26615/978-954-452-049-6_029
DOI:
10.26615/978-954-452-049-6_029
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PDF:
https://doi.org/10.26615/978-954-452-049-6_029