Quantifying and visualizing deliberative dialogue quality in online social spaces

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.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois Urbana-Champaign

Year dc:date

2025

Author dc:creator

• Umashankar, Mukhil

Contributors dc:contributor

• Sundaram, Hari

• Deliberative Dialogue
• Visual Dashboard
• Graph Convolutional Network

Statement dc:rights

• Copyright 2025 Mukhil Umashankar

Language dc:language

en, eng

Handle dc:identifier

https://hdl.handle.net/2142/129627

OAI record oai:identifier

https://www.ideals.illinois.edu/oai-pmh?verb=GetRecord&metadataPrefix=etdms&identifier=oai%3Awww.ideals.illinois.edu%3A2142%2F129627