Faces in the crowd: Twitter as alternative to protest surveys

Christopher Barrie*, Arun Frey

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Who goes to protests? To answer this question, existing research has relied either on retrospective surveys of populations or in-protest surveys of participants. Both techniques are prohibitively costly and face logistical and methodological constraints. In this article, we investigate the possibility of surveying protests using Twitter. We propose two techniques for sampling protestors on the ground from digital traces and estimate the demographic and ideological composition of ten protestor crowds using multidimensional scaling and machine-learning techniques. We test the accuracy of our estimates by comparing to two in-protest surveys from the 2017 Women’s March in Washington, D.C. Results show that our Twitter sampling techniques are superior to hashtag sampling alone. They also approximate the ideology and gender distributions derived from on-the-ground surveys, albeit with some bias, but fail to retrieve accurate age group estimates. We conclude that online samples are yet unable to provide reliable representative samples of offline protest.
Original languageEnglish
Article numbere0259972
Pages (from-to)1-18
Number of pages18
JournalPLoS ONE
Volume16
Issue number11
DOIs
Publication statusPublished - 18 Nov 2021

Keywords

  • Twitter
  • cities
  • age groups
  • social media
  • cartography
  • Arabic people
  • district of Cumbria
  • survey research

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