Date of Award
2020
Document Type
Dissertation
Degree Name
Ph.D.
Organizational Unit
Morgridge College of Education, Research Methods and Information Science, Research Methods and Statistics
First Advisor
Denis Dumas
Second Advisor
Christina Foust
Third Advisor
Duan Zhang
Keywords
Collective action, Confirmatory factor analysis, Connective action, Contentious politics, Digital media, Social movement studies
Abstract
Many protest movements from the last twenty-first century have become increasingly networked and personalized. Several scholars have tapped into this change coining terms such as participatory action, digitally mediated action, computer-mediated communication, issue-based organization, and what I focus on in this project, connective action. Building on the ideas percolating across the literary landscape at the time, Bennett and Segerberg (2012) introduced the logic of connective action based on emergent characteristics they observed in post-2010 large-scale social movements. Both the logic of connective action and related work have become deeply ingrained in today's social movement scholarship. As such, I felt it made logical sense to empirically test the assumptions that are notable shifts in the conversational practices and tactics of movements led by tech-savvy activists when compared to collective action movements.
In my dissertation, I examined the processual patterns of individual activist participation by modeling Bennett and Segerberg's (2012) logic using a novel psychologically-based approach that combined social media content analysis and confirmatory factor analysis (CFA). To build and test my model, I analyzed tweet streams from 184 activists involved in the Black Lives Matter (BLM) movement. The purpose of this study was to demonstrate how connective action can be operationalized through quantification, illustrate how in-situ data sources can be used for statistical modeling, and provide a resource for activists interested in their use of social media to enact social change.
Insights from the content analysis portion include two theoretically contributive terms: Crowd-level identity building (individuals rhetorically maintaining group identity through collective language that is not entirely inclusive nor completely restricted to a shared ideology) and connective consequences (the risks one takes and repercussions they may face as a result of their digital activism), which can help in broadening our understandings of hybrid activist organizing. Findings from the CFA section reveal a unidimensional model as the best fitting model for measuring BLM activists’ connective action, contributing to a clearer sense of this phenomenon and providing empirical evidence for its existence in contemporary social movements. Besides being valuable on their own, my results also offer many opportunities for future research.
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Paige Alfonzo
Provenance
Received from ProQuest
File Format
application/pdf
Language
en
File Size
267 p.
Recommended Citation
Alfonzo, Paige, "Measuring the Connective Action of Black Lives Matter Activists: A Psychometric Investigation into Twitter Data" (2020). Electronic Theses and Dissertations. 1712.
https://digitalcommons.du.edu/etd/1712
Copyright date
2020
Discipline
Communication, Social psychology, Macroecology
Included in
Communication Technology and New Media Commons, Social Media Commons, Social Psychology Commons, Social Statistics Commons, Statistical Models Commons