A Large Open Dataset from the Parler Social Network

Authors

  • Max Aliapoulios New York University
  • Emmi Bevensee Social Media Analysis Toolkit
  • Jeremy Blackburn Binghamton University
  • Barry Bradlyn University of Illinois at Urbana-Champaign
  • Emiliano De Cristofaro University College London
  • Gianluca Stringhini Boston University
  • Savvas Zannettou Max Planck Institute for Informatics

Keywords:

Social network analysis; communities identification; expertise and authority discovery, Qualitative and quantitative studies of social media

Abstract

Parler is as an ``alternative'' social network promoting itself as a service that allows to ``speak freely and express yourself openly, without fear of being deplatformed for your views.'' Because of this promise, the platform become popular among users who were suspended on mainstream social networks for violating their terms of service, as well as those fearing censorship. In particular, the service was endorsed by several conservative public figures, encouraging people to migrate from traditional social networks. After the storming of the US Capitol on January 6, 2021, Parler has been progressively deplatformed, as its app was removed from Apple/Google Play stores and the website taken down by the hosting provider. This paper presents a dataset of 183M Parler posts made by 4M users between August 2018 and January 2021, as well as metadata from 13.25M user profiles. We also present a basic characterization of the dataset, which shows that the platform has witnessed large influxes of new users after being endorsed by popular figures, as well as a reaction to the 2020 US Presidential Election. We also show that discussion on the platform is dominated by conservative topics, President Trump, as well as conspiracy theories like QAnon.

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Published

2021-05-22

How to Cite

Aliapoulios, M., Bevensee, E., Blackburn, J., Bradlyn, B., De Cristofaro, E., Stringhini, G., & Zannettou, S. (2021). A Large Open Dataset from the Parler Social Network. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 943-951. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18117