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Stuart Duncan

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Computational Social Science

My research has employed computational methods to study social science issues. Leveraging my background in computer science, I have relied on my programming and digital skills to analyze social science issues that would be challenging to research using human-based research methods alone. Using tools such as Python, Flask, Django, and SQL, I have also become quite adept at creating digital tools for audience research. I have also used Python as a data manipulation tool, preparing large datasets for analysis. Using web scraping techniques and accessing publicly available APIs has provided me with invaluable data sources for academic research.

Related Projects:

  • NEWSFLOWS: Research Internship
    As part of my coursework in the PhD in Media and Design program, I undertook an internship working with Dr. Damian Trilling at the…
  • News Personalization: Do Journalism Audiences Prefer Algorithms Over Editors?
    My final project-paper as part of my Master’s in Communication and Culture explores what motivates news organizations to employ algorithmically driven news personalization techniques…
  • An Automated Approach to Measuring Online Deliberation
    This project proposes a framework for an automated method to measure online deliberation by analyzing commentary surrounding a complex social issue. By employing a…

Contact

Email : stuart@stuartduncan.ca

Twitter : @stuartbduncan

YouTube : @stuart.duncan

Mastodon : @stuartbduncan@hci.social

Github : stuartduncan416

© 2025 Stuart Duncan