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Faces in the crowd: Twitter as alternative to protest surveys
Christopher Barrie1, Arun Frey2,3
1School of Social & Political Science, University of Edinburgh, Scotland, United Kingdom.
Plos One
|November 18, 2021
Summary
Researchers explored using Twitter to survey protest participants, finding it superior to hashtag sampling but not yet a reliable method for representative offline protest samples.
Area of Science:
- Social Sciences
- Computational Social Science
- Political Science
Background:
- Traditional methods for surveying protest participants, such as retrospective population surveys or in-person surveys, are costly and logistically challenging.
- These existing methods face significant methodological constraints, limiting their scalability and scope.
Purpose of the Study:
- To investigate the feasibility of using Twitter data for surveying protest participants.
- To develop and evaluate novel techniques for sampling protestors using digital traces from Twitter.
- To estimate the demographic and ideological composition of protest crowds via online data.
Main Methods:
- Proposed two techniques for sampling protestors from Twitter digital traces.
- Employed multidimensional scaling and machine-learning techniques to estimate crowd composition.
- Validated estimates against in-person survey data from the 2017 Women's March.
Main Results:
- Twitter sampling techniques demonstrated superiority over simple hashtag sampling.
- Online samples approximated ideology and gender distributions found in on-the-ground surveys, though some bias was observed.
- Estimates of age group distributions were found to be inaccurate.
Conclusions:
- Online samples derived from Twitter show promise for understanding protestor characteristics.
- Current methods are insufficient for generating reliable, representative samples of offline protestor populations.
- Further methodological advancements are needed to overcome biases and improve accuracy in online protestor sampling.
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