Quantifying and visualizing deliberative dialogue quality in online social spaces
Umashankar, Mukhil
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Permalink
https://hdl.handle.net/2142/129627
Description
Title
Quantifying and visualizing deliberative dialogue quality in online social spaces
Author(s)
Umashankar, Mukhil
Issue Date
2025-05-06
Director of Research (if dissertation) or Advisor (if thesis)
Sundaram, Hari
Department of Study
Siebel School Comp & Data Sci
Discipline
Computer Science
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Deliberative Dialogue
Visual Dashboard
Graph Convolutional Network
Abstract
Social media spaces empower individuals to ideate, iterate, and refine their thinking through exposure to diverse perspectives and real-time feedback. However, in reality, these benefits are accompanied by toxicity, spam, and polarization. These negative features are especially prevalent in deliberative spaces. The effective functioning of these platforms is crucial for democracies as a substantial volume of public discourse on real-world issues takes place within them. This study offers a quantitative assessment of deliberative dialogue in news spaces, drawing its evaluative metrics from deliberative theory. A mix of linguistic and network-based methods is adopted to compute the indicators. The results of the assessment are presented through user-centric visualizations. The goal is to model deliberative quality and make it accessible to the general audience, recognizing their role in upholding high-standard deliberation.
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