Dissertation Proposal Defense - Shruti Phadke
Towards Analyzing Online Communities of Problematic Information: A Computational Approach
Abstract: Problematic information–information that is inaccurate, misleading, inappropriately attributed, or altogether fabricated–prevails in digital societies and spaces. Communities formed around theorizing or mobilizing problematic information can lead online users through the path of social distrust, paranoia, or radicalization.
Despite the obvious disruptive consequences of online communities of problematic information, we don't have a large-scale, data-driven understanding of deeper social processes that are underway. In this dissertation, I contribute empirical insights into engagement, mobilization, and disengagement from communities of problematic information using theory-guided quantitative methods. My research takes me across multiple social media platforms such as Reddit, Facebook, Twitter, 4chan, and various methodologies from machine learning, and natural language processing to qualitative interviews. In this dissertation, I describe my analysis of various instances of problematic information, such as conspiracy theories and hate movements in the West. Specifically, I ask:
(1) What makes people engage in conspiracy theory discussions?
(2) What are the mechanisms of information mobilization and content framing in online hate movements?
(3) What are the ways in which people may leave online conspiracy theory discussions?
Given the Western focus of my completed work, I further propose extending my methods to observe how mechanisms of mobilization of problematic information evolve outside the USA. Moreover, I will also outline my plans to interview former conspiracy theory believers to gain deeper causal insights into disengagement from online conspiracy theory discussions. I will conclude by briefly outlining the future implications of designing technological interventions to reduce participation in problematic communities online.
Chair: Dr. Tanu Mitra, Assistant Professor, iSchool
GSR: Dr. David Ribes, Associate Professor, HCDE
Member: Dr. Emma Spiro, Associate Professor, iSchool
Member: Dr. Kate Starbird, Associate Professor, HCDE