Data: Timely identification of event start dates from Twitter

DOI

This directory features data that is discussed in the paper: F. Kunneman, A. Hürriyetoglu, N. Oostdijk and A. Van den Bosch (2014), Timely identification of event start dates from Twitter, Computational Linguistics in the Netherlands Journal, 4, pp. 39-52, http://hdl.handle.net/2066/135169This paper describes a study to automatically identify the date of a social event based on tweets that refer to it in anticipation, as early as possible. This data set comprises of the tweetids that refer to 60 football events and 5 events of other types by means of a hashtag or the name of the event. These tweets were used to train and test different approaches to identifying the event date long before the event starts. In addition to the tweetids, we give the number of days until the event at the time when each tweet is posted, and the time references that could be extracted from each tweet.

Identifier
DOI https://doi.org/10.17026/dans-z8e-3uqb
Metadata Access https://ssh.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-z8e-3uqb
Provenance
Creator F.A. Kunneman; A. Hürriyetoğlu; N.H.J. Oostdijk; A.P.J. van den Bosch
Publisher DANS Data Station Social Sciences and Humanities
Contributor RU Radboud University
Publication Year 2017
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
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Version 2.0
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences