Toward a computational mixed methods framework to measure online deliberative discourse
This article proposes and tests a reproducible framework for a computational method to measure social media-based deliberative discourse by analyzing commentary surrounding the Canadian convoy protests of COVID-19 vaccine mandates and restrictions. Employing a combination of analytic calculations, alongside tools such as Google Perspective and Linguistic Inquiry and Word Count (LIWC), this article assesses the quality of online deliberative discourse using established measures of deliberation including the variables rationality, interactivity, equality, and civility. We propose computational approaches to measuring these variables, and work toward validating our approach by observing correlations between an established computational measure of online deliberation-cognitive complexity. This computational approach is tested using Twitter and Reddit commentary related to the convoy protests that took place in Ottawa, Canada, during February 2022, which influenced the emergence of similar protests around the world. In addition to testing our proposed online deliberative discourse measurement framework, this case study provides insight into the deliberative characteristics of the Twitter and Reddit social media platforms.
Authors
- Lauren Dwyer
- H. Jesse Smith
- Charles Davis
- Davis Vallesi
- Frauke Zeller (ORCID: https://orcid.org/0000-0001-6835-2529)
- Stuart Duncan (ORCID: https://orcid.org/0000-0002-4845-1594)
Institutions
- York University (CA)
- Edinburgh Napier University (GB)
- Toronto Metropolitan University (CA)
- Mount Royal University (CA)
Publication Details
- Journal
- Communication and the Public
- Published
- 2024-10-06
- DOI
- https://doi.org/10.1177/20570473241284759
- Citations
- 3
- Primary Topic
- Social Media and Politics
- Type
- article
- Field-Weighted Citation Impact
- 2.87
Funders
- Social Sciences and Humanities Research Council of Canada