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      Dataset: tweets and analyses related to the paper 'The (Un)Predictability of Emotional Hashtags in Twitter'

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      Creators
      Kunneman, F.A.
      Liebrecht, C.C.
      Bosch, A.P.J. van den
      Date of Archiving
      2017
      Archive
      DANS EASY
      DOI
      https://doi.org/10.17026/dans-zs9-fj3t
      Related publications
      The (un)predictability of emotional hashtags in Twitter   -
      Publication type
      Dataset
      Please use this identifier to cite or link to this item: https://hdl.handle.net/2066/174262   https://hdl.handle.net/2066/174262
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      Organization
      Communicatie- en informatiewetenschappen
      Audience(s)
      Communication sciences
      Languages used
      Dutch; English
      Key words
      Twitter; Emotion; Natural Language Processing; Document Classification; Machine Learning; Emotion Detection
      Abstract
      This dataset features all the tweetids and labels that were used to model the language of 24 hashtags, and test the performance on predicting the hashtags in unseen tweets. This study is described in: Kunneman, F.A., Liebrecht, C.C. & Bosch, A.P.J. van den (2014). The (Un)Predictability of Emotional Hashtags in Twitter. In Proceedings of the 5th Workshop on Language Analysis for Social Media (LASM) @ EACL 2014 (pp. 26-34). s.l.: Association for Computational Linguistics, http://hdl.handle.net/2066/127067 In addition to the train and test data, this dataset includes the most indicative features (words and phrases) for four of the hashtags, as well as the human judgement whether the tweets that contain or are classified with these hashtags convey the presumed emotion of the hashtags. Subject period: December 16th 2010 until February 1st 2013
      This item appears in the following Collection(s)
      • Datasets [1485]
      • Faculty of Arts [28799]
       
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