Michael Carelse
My Role:
As a Research & Instruction Librarian, I conduct library instruction sessions, provide research consultations, and perform collection management duties in my liaison areas. I am the subject librarian for the Department of Communication Sciences and Disorders, the Department of Criminal Justice and Legal Studies, the Department of Nutrition and Hospitality Management, and the Department of Social Work.
Education:
MLIS University of British Columbia
MA University of Victoria
BA University of Victoria
Selected Publications and Presentations:
Publications:
Carelse, M. (2023). Unique forms of ekphrasis: The Keepsake and the illustrative poetry of the literary annuals. Victorian Poetry 61(3), 301-335. https://dx.doi.org/10.1353/vp.2023.a915653
Presentations:
Carelse, M. (2023, June 28-July 1). Records management and social justice: Scrutinizing the RCMP’s records retention policies [Conference presentation]. Association of Canadian Archivists, Charlottetown, PEI, Canada.
Carelse, M. (2023, February 27). For the record(ed): Frameworks for human-centred archival practice [Public talk]. Green College Resident Members’ Series, Vancouver, BC, Canada. https://www.youtube.com/watch?v=fQU5yq0PC-Y
Carelse, M. (2019, November 7-9). Impressionism and narrative caution in Thomas Hardy’s The Woodlanders [Conference presentation]. Victorian Interdisciplinary Studies Association of the Western United States, Seattle, WA, United States.
Carelse, M. (2019, May 1-3). The Hand of Ethelberta: Thomas Hardy’s antisocial novel [Conference presentation]. Victorian Studies Association of Western Canada. Calgary, AB, Canada.
Sian Lee
My Role:
As an Assistant Professor of Scholar Support and Data Services (SSDS), I teach computational methods that enhance the research capabilities of faculty, staff, and students while fostering digital literacy. My research focuses on computational social science, investigating the intersection of computational methods and human behavior analysis. Specifically, I apply data science techniques—including Statistical Inference, Natural Language Processing, Machine Learning, and Deep Learning—to understand, analyze, and predict human decision-making and behavior.
Research Interests:
Computational Social Science, Misinformation, Applied Natural Language Processing / Machine Learning / Deep Learning, Experiments
Education:
- Ph.D. in Informatics, minor in Statistics, College of Information Sciences and Technology, Pennsylvania State University
- M.A. in Economics, Korea University and Pennsylvania State University
- B.A. in Economics and International and Area Studies, Handong Global University
Selected Publications:
- Seo, H., Lee, S., Xiong, A., & Lee, D. (2024). Reliability Matters: Exploring the Effect of AI Explanations on Misinformation Detection With a Warning. In Proceedings of the International AAAI Conference on Web and Social Media, 18(1), 1395–1407.
- Lee, S., Xiong, A., Seo, H., & Lee, D. (2023). “Fact-Checking” Fact-Checkers: A Data-Driven Approach. Harvard Kennedy School (HKS) Misinformation Review, 4(5).
- Lee, S., Seo, H., Xiong, A., & Lee, D. (2023). Associative Inference Can Increase People’s Susceptibility to Misinformation. In Proceedings of the International AAAI Conference on Web and Social Media, 17(1), 530–541.
- Xiong, A., Lee, S., Seo, H., & Lee, D. (2023). Effects of associative inference on individuals’ susceptibility to misinformation. Journal of Experimental Psychology: Applied, 29(1), 1–17.
- Seo, H., Xiong, A., Lee, S., & Lee, D. (2022). If You Have a Reliable Source, Say Something: Effects of Correction Comments on COVID-19 Misinformation. In Proceedings of the International AAAI Conference on Web and Social Media, 16(1), 896–907.
- Seo, H., Xiong, A., Lee, S., & Lee, D. (2021). (In)effectiveness of Accumulated Correction on COVID-19 Misinformation. In Technology, Mind, and Behavior Proceedings 2021.
- Lee, S., Forrest, J., Strait, J., Seo, H., Lee, D., & Xiong, A. (2020). Beyond cognitive ability: Susceptibility to fake news is also explained by associative inference. In Late-Breaking Works of the 2020 CHI Conference on Human Factors in Computing Systems, 1–8.
Committees:
- Interdisciplinary Graduate Minor in Applied Statistics (GMAS) Committee
- Library Digital Scholarship Committee
- Library Artificial Intelligence Committee
Workshops Taught:
- Introduction to LaTeX / Overleaf
- Building a Resume/CV with Overleaf/LaTeX
- Introduction to Google Colab: Using Generative AI for Python Programming
- Text Data Analysis for Beginners Using Python and Kaggle Dataset (Workshop Series)
- Python Intermediate (Workshop Series)
- Social Media Data Collection using Python PRAW: How to Use the Reddit API to Collect Data for Research (Workshop Series)