A Dataset of State-Censored Tweets


  • Tuğrulcan Elmas EPFL
  • Rebekah Overdorf EPFL
  • Karl Aberer EPFL




Qualitative and quantitative studies of social media, Credibility of online content, Trust; reputation; recommendation systems, Social network analysis; communities identification; expertise and authority discovery


Many governments impose traditional censorship methods on social media platforms. Instead of removing it completely, many social media companies, including Twitter, only withhold the content from the requesting country. This makes such content still accessible outside of the censored region, allowing for an excellent setting in which to study government censorship on social media. We mine such content using the Internet Archive's Twitter Stream Grab. We release a dataset of 583,437 tweets by 155,715 users that were censored between 2012-2020 July. We also release 4,301 accounts that were censored in their entirety. Additionally, we release a set of 22,083,759 supplemental tweets made up of all tweets by users with at least one censored tweet as well as instances of other users retweeting the censored user. We provide an exploratory analysis of this dataset. Our dataset will not only aid in the study of government censorship but will also aid in studying hate speech detection and the effect of censorship on social media users. The dataset is publicly available at https://doi.org/10.5281/zenodo.4439509




How to Cite

Elmas, T., Overdorf, R., & Aberer, K. (2021). A Dataset of State-Censored Tweets. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 1009-1015. https://doi.org/10.1609/icwsm.v15i1.18124