2026-04-16T06:51:48Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

b1291d7e8efcee32a9197fea9fd9b876a9fb174dbb8ba511392d7119ab4d6666 2025-12-08T01:50:59Z language:enopenaire_data

Data: Timely identification of event start dates from Twitter Data: Timely identification of event start dates from Twitter doi:10.17026/DANS-Z8E-3UQBRadboud MetisID 552951easy-dataset:68090 F.A. Kunneman A. Hürriyetoğlu N.H.J. Oostdijk A.P.J. van den Bosch 2017-01-01 DANS Data Station Social Sciences and Humanities 2017-01-18 Computer and Information ScienceSocial SciencesNatural Language ProcessingSocial MediaMachine LearningTwitterSocial eventsTimeTime Expressions <p>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/2066/135169</p><p>This 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.</p> https://ssh.datastations.nl/oai doi:10.17026/DANS-Z8E-3UQB 2025-12-03T01:00:46Z ddi:codebook:2_5