research data . Dataset . 2016

Webis Clickbait Corpus 2016 (Webis-Clickbait-16)

Potthast, Martin; Stein, Benno; Hagen, Matthias; Köpsel, Sebastian;
Open Access English
  • Published: 23 Mar 2016
  • Publisher: Zenodo
Abstract
<p>The Webis Clickbait Corpus 2016 (Webis-Clickbait-16) comprises 2992 Twitter tweets sampled from top 20 news publishers as per retweets in 2014. The tweets have been manually annotated by three independent annotators with regard to whether they can be considered clickbait. A total of 767 tweets are considered clickbait by the majority of annotators. The majority vote of reviewers can be used as a ground truth to build clickbait detection technology. This corpus is the first of its kind and gives rise to the development of technology to tackle clickbait.</p>
Subjects
free text keywords: clickbait, click, bait, detection, Cell Biology, Genetics, Ecology, Immunology, Developmental Biology, Science Policy, Plant Biology, Space Science, 59999 Environmental Sciences not elsewhere classified, 69999 Biological Sciences not elsewhere classified, 80699 Information Systems not elsewhere classified
Communities
Science and Innovation Policy Studies
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Zenodo
Dataset . 2016
Provider: Datacite
Zenodo
Dataset . 2016
Provider: Datacite
Zenodo
Dataset . 2016
Provider: Zenodo
figshare
Dataset . 2016
Provider: figshare
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