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2 datasets found
  1. Webis Clickbait Corpus 2016 (Webis-Clickbait-16)

    • zenodo.org
    • webis.de
    • +1more
    zip
    Updated Jun 11, 2022
  2. W

    Webis-Clickbait-17

    • webis.de
    5530410
    Updated 2017
    + more versions
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Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Matthias Hagen; Matthias Hagen; Sebastian Köpsel; Sebastian Köpsel (2022). Webis Clickbait Corpus 2016 (Webis-Clickbait-16) [Dataset]. http://doi.org/10.5281/zenodo.3251557
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Webis Clickbait Corpus 2016 (Webis-Clickbait-16)

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zipAvailable download formats
Dataset updated
Jun 11, 2022
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Matthias Hagen; Matthias Hagen; Sebastian Köpsel; Sebastian Köpsel
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

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.

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