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  • Research data . 2017
    Open Access Dutch
    Authors: 
    Kunneman, F.A.; Hürriyetoğlu, A.; Oostdijk, N.H.J.; Bosch, A.P.J. Van Den;

    doi: 10.17026/dans-z8e-3uqb

    handle: 2066/166570

    Publisher: Data Archiving and Networked Services (DANS)
    Country: Netherlands

    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 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.

    Average popularity
    Average popularity In bottom 99%
    Popularity: Citation-based measure reflecting the current impact.
    Average influence
    Average influence In bottom 99%
    Influence: Citation-based measure reflecting the total impact.
    addAdd to  ORCID orcid 
Advanced search in Research products
Research products
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Simple Search
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The following results are related to Digital Humanities and Cultural Heritage. Are you interested to view more results? Visit OpenAIRE - Explore.
1 Research products, page 1 of 1
  • Research data . 2017
    Open Access Dutch
    Authors: 
    Kunneman, F.A.; Hürriyetoğlu, A.; Oostdijk, N.H.J.; Bosch, A.P.J. Van Den;

    doi: 10.17026/dans-z8e-3uqb

    handle: 2066/166570

    Publisher: Data Archiving and Networked Services (DANS)
    Country: Netherlands

    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 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.

    Average popularity
    Average popularity In bottom 99%
    Popularity: Citation-based measure reflecting the current impact.
    Average influence
    Average influence In bottom 99%
    Influence: Citation-based measure reflecting the total impact.
    addAdd to  ORCID orcid