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Abstract
Social movements can be understood through their use of collective action frames, construction of collective identities, and deployment of emotions. To operationalize this theory, abduction is a framework that is suited for multi-method investigations in order to respond to research questions that include elements of both quantitative and qualitative sensibilities. In this dissertation, I focus on the implications of sampling itself, bridging abduction and grounded theory to offer the notion of computationally assisted theoretical sampling, consisting of: (1) familiarization, (2) categorization, (3) comparison, and (4) refinement. Two discrete case studies using this framework were completed to demonstrate the utility of this approach. The first examines the ways in which a conservative countermovement formed a public identity against feminism centering Alt-Right leader, Milo Yiannopoulos. Within the balance of emotionally polarized content, negative claims of identity (i.e., hatred) consolidated the self-presentation of supporters. The second case study investigated how the 2017 Women’s Marches launched a platform of resistance under the Trump administration. As an initiator movement, the frames used to articulate the Women’s Marches emphasized recruitment, including (1) amplifying tensions in response to emergent threats, (2) sustaining action through an enduring opposition, and (3) launching activists into new types of action. The findings from this project can inform future research in the realm of social movements, social media studies, and methodology.
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