Dataset Open Access

Webis Clickbait Corpus 2016 (Webis-Clickbait-16)

Potthast, Martin; Stein, Benno; Hagen, Matthias; Köpsel, Sebastian


Citation Style Language JSON Export

{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.3251557", 
  "language": "eng", 
  "title": "Webis Clickbait Corpus 2016 (Webis-Clickbait-16)", 
  "issued": {
    "date-parts": [
      [
        2016, 
        3, 
        23
      ]
    ]
  }, 
  "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>", 
  "author": [
    {
      "family": "Potthast, Martin"
    }, 
    {
      "family": "Stein, Benno"
    }, 
    {
      "family": "Hagen, Matthias"
    }, 
    {
      "family": "K\u00f6psel, Sebastian"
    }
  ], 
  "id": "3251557", 
  "type": "dataset", 
  "event": "38th European Conference on IR Research (ECIR 2016)"
}
230
52
views
downloads
All versions This version
Views 230230
Downloads 5252
Data volume 13.9 GB13.9 GB
Unique views 215215
Unique downloads 4545

Share

Cite as