Ph.D. (Doctor of Philosophy)
Department of English
Algorithms are ubiquitous components of digital age rhetoric and communication. Although they are integrated within our daily online functions, shaping our discourse and interactions with one another and with other algorithms, little is known how they shape rhetorical agency. Most of our online communication occurs through social media on platforms such as Facebook and Twitter, and we rely on social spaces like Wikipedia for updated information that is shaped by social constructs. We presume that since we program algorithms, their communicating functions mimic human discourse and can be shaped similarly.
However, a rich text analysis of three different case studies look at how algorithms vary in how they alter rhetorical agency—shaping discourse, power structures, and interactions in ways we have not seen before. Through this analysis and visualized with ontographs – geographic maps that show the distribution of actant interactions within an environment – the distribution of agency is traced between actants and compared to more traditional systems of human-to-human communication to tease out how algorithms behave differently.
This research examines the case study of the Facebook [loveMachine], an “art bot” that was created to provoke discussion about what the Facebook “like” button really means; a Twitter botnet dubbed the “Peñabots” that shaped a political election and presidency in Mexico; and the Wikipedia Addbot, which automated tens of thousands of “reverts” on the platform. Each case study offers a unique look at the rhetorical function of the social media bot algorithms within different platforms.
Geiger, Aaron, "Disruption, Remix, and Mediation: Analyzing "Bot" Algorithm Case Studies to Better Understand Rhetorical Agency in the Digital Age" (2019). Graduate Research Theses & Dissertations. 7059.
Northern Illinois University
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