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.
","abstract_html":"<p>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.</p> <p>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.</p> <p>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.</p>","abstract_has_math":false,"creators":["Alfonzo, Paige"],"institution":null,"degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Denis Dumas","Christina Foust","Duan Zhang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-01-01T08:00:00Z","date_published":"2020-01-01T08:00:00Z","updated_at":"2026-07-24T02:03:12Z","subjects":["Collective action","Confirmatory factor analysis","Connective action","Contentious politics","Digital media","Social movement studies","Communication Technology and New Media","Social Media","Social Psychology","Social Statistics","Statistical Models","Statistics and Probability"],"languages":["en"],"rights":["Copyright is held by the author. User is responsible for all copyright compliance.
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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.
"]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Measuring the Connective Action of Black Lives Matter Activists: A Psychometric Investigation into Twitter Data"]}]}],"canonical_facts":{"dc:contributor":["Denis Dumas","Christina Foust","Duan Zhang"],"dc:creator":["Alfonzo, Paige"],"dc:date.available":["2022-10-02T07:00:00Z"],"dc:description.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.
"],"dc:format":["application/pdf"],"dc:identifier":["https://digitalcommons.du.edu/etd/1712"],"dc:language":["en"],"dc:rights":["Copyright is held by the author. User is responsible for all copyright compliance.
"],"dc:subject":["Collective action","Confirmatory factor analysis","Connective action","Contentious politics","Digital media","Social movement studies","Communication Technology and New Media","Social Media","Social Psychology","Social Statistics","Statistical Models","Statistics and Probability"],"dc:title":["Measuring the Connective Action of Black Lives Matter Activists: A Psychometric Investigation into Twitter Data"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T02:03:12Z"}