Supplementary and replication materials for the paper
"Voting and Social Media-Based Political Participation"
This repository contains supplementary and replication materials for the paper "Voting and Social Media-Based Political Participation" by Sascha Göbel, published in Journal of Quantitative Description: Digital Media.
Does online political involvement reinforce or compensate participatory deficiencies at the polls? Extant survey evidence portrays online participation as a weapon of the strong, wielded by a highly politically involved, white, and affluent subset of the American electorate. Surveys face systematic sampling and measurement errors in the domain of political participation, though. In this study, I revisit this question using individual voter registration records that I integrate with observed Twitter activity. Based on a large sample that reflects Florida’s voting-eligible population, I find that political involvement on Twitter is prevalent across the electorate and extends to those most likely to abstain from voting. Moreover, race and income, which are salient dividing lines in voting, do not structure social media-based political participation and common turnout patterns for age, and party subgroups are reversed, though especially among more engaged voters. These results offer a novel perspective on reinforcement theory and social media’s compensatory potential for more inclusive representation. I discuss implications for political representation and future research examining political involvement.
- Code: contains R code for data collection and processing, analyses, and figures.
- Data: contains anonymized replication data for main analyses (serialized).
- Figures: contains all figures presented in the paper and appendix.
Voter record and Twitter Text data used in this paper are too large to be stored here. In addition, there exist both ethical and legal restrictions that prohibit directly sending to or publicly sharing these data with third parties. Offering anonymized replication data decoupled from information that would allow future re-identification of individuals while retaining full individual text messages is not possible. For researchers wishing to replicate the analyses in the paper (beyond what's possible with the basic replication file) or to collaborate based on these data in a strictly non-commercial setting, data access is only possible via a non-disclosure agreement with the author and in accordance with Twitter regulations.
Sascha Göbel
Goethe University Frankfurt
Faculty of Social Sciences
60323 Frankfurt am Main, Germany
Email: sascha.goebel [at] soz.uni-frankfurt.de