Terrorism on Twitter: Using topic models to examine topoi and digital rituals following mass violence

Pitchford, Matthew C

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https://hdl.handle.net/2142/110727 Copy

Description

Title

Terrorism on Twitter: Using topic models to examine topoi and digital rituals following mass violence

Author(s)

Pitchford, Matthew C

Issue Date

2021-04-22

Director of Research (if dissertation) or Advisor (if thesis)

O'Gorman, Ned

Doctoral Committee Chair(s)

O'Gorman, Ned

Committee Member(s)

• Poole, Scott
• Cisneros, David
• Underwood, Ted

Department of Study

Communication

Discipline

Communication

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• topoi
• digital rhetoric
• publics
• computational methods
• Twitter

Abstract

I argue that “algorithmic publics” are an important addition to our theories of publics and their formation. Publics are constituted by attention to the reflexive circulation of texts, performances, and affect. Digital spaces, however, seem to overwhelm our traditional practices and patterns of attention due to speed and number of things to which we can pay attention. Scholars should think of digital publics as algorithmic publics, ephemeral publics formed by the direction of attention between human and encoded actors, such as when humans use hashtags to find and discuss ideas with each other in context of the Twitter trending algorithm. This turn to algorithmic publics considers the materiality of algorithms and interfaces and the infrastructures that direct our attention online. I further argue that scholars should deploy new methods to apprehend and understand algorithmic publics. I argue that computational methods can be an effective method to identify and analyze public expressions as they are concretized in language, ritualistically enacted through interfaces, and given topical form and structure through topoi. In particular, I deploy topic modeling as a computational method to identify linguistic patterns of discourse present in Twitter responses to three highly publicized mass violence events: the 2013 Boston Marathon Bombing, the 2015 Charleston church shooting, and the 2016 Orlando Nightclub shooting. I find that although each event represents a different algorithmic public and contains distinct political, cultural, and affective emphases, there are some important similarities between each in the form of consistent topoi: 1) grief and eulogy, 2) reconstituting community, and 3) identifying motives. The first, and by far the most prevalent of the three commonplaces, is language about grief, mourning, eulogy, and “thoughts and prayers.” On this affective and emotional level, thoughts and prayers have performative and rhetorical significance by providing scripts to grieve, mourn, and eulogize together. The second topos focused on the ritualized reconstitution of communities, whether based on geography, identity, or political affiliation. In light of trauma, crisis, and highly publicized mass violence, individuals seek to rearticulate the relationships that tie them together. Finally, there were topoi focused on the “why” of the attack—discourses about motivation. Sometimes these topoi were focused on information seeking about the identity of the attacker(s) or using contextual clues to make claims about their identity. But regardless of their form, these topoi were about making sense of the attacker’s actions in the context of larger societal structures. This discourse is about where we can find understanding and, in turn, place explanation and blame: in the individual, in the tools that make the attack possible, or in their system of beliefs. Taken together, these topoi demonstrate how algorithmic publics function and have the power to direct attention and shape political discourse through the material, cultural, and institutional forces that compose the digital network. We return to these topoi because they consistently provide affective, argumentative, and political rituals to explain, give solace, and bring together communities following traumatic events.

Graduation Semester

2021-05

Type of Resource

Thesis

Permalink

http://hdl.handle.net/2142/110727

Copyright and License Information

Copyright 2021 Matthew Pitchford

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