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Dataset for: "How over is it?" Understanding the Incel Community on YouTube

Kostantinos Papadamou; Savvas Zannettou; Jeremy Blackburn; Emiliano De Cristofaro; Gianluca Stringhini; Michael Sirivianos


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4557039", 
  "title": "Dataset for: \"How over is it?\" Understanding the Incel Community on YouTube", 
  "issued": {
    "date-parts": [
      [
        2021, 
        3, 
        22
      ]
    ]
  }, 
  "abstract": "<p><strong>Dataset for the paper: &quot;How over is it?&quot; Understanding the Incel Community on YouTube</strong></p>\n\n<p><strong>Abstract:</strong>&nbsp;YouTube is by far the largest host of user-generated video content worldwide.&nbsp;Alas, the platform also hosts inappropriate, toxic, and hateful content.&nbsp;One community that has often been linked to sharing and publishing hateful and misogynistic content is the so-called Involuntary Celibates (Incels), a loosely defined movement ostensibly focusing on men&#39;s issues.&nbsp;In this paper, we set out to analyze the Incel community on YouTube by focusing on this community&#39;s evolution over the last decade and understanding whether YouTube&#39;s recommendation algorithm steers users towards Incel-related videos.&nbsp;We collect videos shared on Incel communities within Reddit and perform a data-driven characterization of the content posted on YouTube.&nbsp;Among other things, we find that the Incel community on YouTube is getting traction and that during the last decade, the number of Incel-related videos and comments rose substantially.&nbsp;We also find that users have a 6.3% chance of being suggested an Incel-related video by YouTube&#39;s recommendation algorithm within five hops when starting from a non-Incel-related video.&nbsp;Overall, our findings paint an alarming picture of online radicalization: not only Incel activity is increasing over time, but platforms may also play an active role in steering users towards such extreme content.</p>\n\n<p><strong>Dataset Files</strong></p>\n\n<p>The dataset consists of nine&nbsp;files, which include the metadata, comments, and captions of all the videos collected and analyzed in this paper (Incel-derived set, Control Set, Incel-derived Recommendation Graph, and Control Recommendation Graph), as well as the Incel Terms lexicon that we use in our video annotation methodology.</p>\n\n<p><strong>1. Video Metadata</strong></p>\n\n<ul>\n\t<li><strong>&quot;incel_derived_groundtruth_videos.json&quot;:</strong>&nbsp;Contains the Incel-derived labeled ground-truth videos shared in Incel-related subreddits on Reddit. It includes 6,452 videos (290 Incel-related and 6,162 &quot;Other&quot;) annotated following the video annotation methodology described in the paper.</li>\n\t<li><strong>&quot;control_groundtruth_videos.json&quot;:</strong> Contains the randomly selected YouTube videos shared in various subreddits on Reddit. It includes 5,793 videos (66 Incel-related and 5,727 &quot;Other&quot;)&nbsp;annotated following the video annotation methodology described in the paper.</li>\n\t<li><strong>&quot;incel_derived_recommendation_graph_videos.json&quot;:</strong> Contains the 37.7K YouTube videos used to construct the Incel-derived recommendation graph. We have 1,074 Incel-related videos and 36,673 &quot;Other&quot; videos annotated&nbsp;following the video annotation methodology described in the paper.</li>\n\t<li><strong>&quot;control_recommendation _graph_videos.json&quot;:</strong>&nbsp;Contains the 29.3K YouTube videos used to construct the Control recommendation graph. We have 428 Incel-related videos and 28,866 &quot;Other&quot; videos annotated following the video annotation methodology described in the paper.</li>\n</ul>\n\n<p><strong>- Video Metadata Description:</strong></p>\n\n<ul>\n\t<li><em>&quot;annotation_label&quot;</em>: The annotation label assigned to the video by&nbsp;our video annotation methodology.</li>\n\t<li><em>&quot;isSeed&quot;</em>: 0 if the video is a seed video in the recommendation graph, 1 if it is a recommended video of a seed video.</li>\n\t<li><em>&quot;relatedVideos&quot;</em>: The recommended videos of the given video as returned by the YouTube Data API.</li>\n</ul>\n\n<p><strong>2. Video Comments:&nbsp;</strong></p>\n\n<ul>\n\t<li><strong>&quot;incel_derived_videos_comments.json&quot;:</strong>&nbsp;Includes the unique identifiers of the comments of the Incel-derived ground-truth&nbsp;and the Incel-derived Recommendation Graph videos.</li>\n\t<li><strong>&quot;control_videos_comments.json&quot;:</strong>&nbsp;Includes the unique identifiers of the comments of the Control ground-truth and the Control Recommendation Graph videos.</li>\n</ul>\n\n<p><strong>3. Video Transcripts:</strong></p>\n\n<ul>\n\t<li><strong>&quot;incel_derived_videos_transcripts.json&quot;:</strong> Includes the captions of&nbsp;the Incel-derived ground-truth&nbsp;and the Incel-derived Recommendation Graph videos.</li>\n\t<li><strong>&quot;control_videos_transcripts.json&quot;:</strong> Includes the captions of the Control ground-truth and the Control Recommendation Graph videos.</li>\n</ul>\n\n<p><strong>4. Incel-related Terms Dictionary:</strong></p>\n\n<ul>\n\t<li><strong>&quot;incel_related_terms_dictionary&quot;:</strong> It includes all the 200 terms of the Incel-related terms lexicon mentioned in the paper and used in our video annotation methodology.</li>\n</ul>\n\n<p>If you use this dataset in any publication, of any form and kind, please cite using this data:</p>\n\n<pre><code>@article{papadamou2020understanding,\n  title={\"How over is it?\" Understanding the incel community on youtube},\n  author={Papadamou, Kostantinos and Zannettou, Savvas and Blackburn, Jeremy and De Cristofaro, Emiliano and Stringhini, Gianluca and Sirivianos, Michael},\n  journal={arXiv preprint arXiv:2001.08293},\n  year={2020}\n}</code></pre>", 
  "author": [
    {
      "family": "Kostantinos Papadamou"
    }, 
    {
      "family": "Savvas Zannettou"
    }, 
    {
      "family": "Jeremy Blackburn"
    }, 
    {
      "family": "Emiliano De Cristofaro"
    }, 
    {
      "family": "Gianluca Stringhini"
    }, 
    {
      "family": "Michael Sirivianos"
    }
  ], 
  "note": "Acknowledgments: This project has received funding from the European Union's Horizon 2020 Research and Innovation program under the Marie Sk\\l{}dowska-Curie ENCASE project (GA No. 691025) and the CONCORDIA project (GA No. 830927), the US National Science Foundation (grants: 1942610, 2114407, 2114411, and 2046590), and the UK's National Research Centre on Privacy, Harm Reduction, and Adversarial Influence Online (UKRI grant: EP/V011189/1). This work reflects only the authors' views; the Agency and the Commission are not responsible for any use that may be made of the information it contains.", 
  "type": "dataset", 
  "id": "4557039"
}
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