My research interests revolve around feminist media and youth studies, critical internet histories, and research ethics. I take a historical perspective to digital technologies and a mixed method approach to studying histories of and about the web. I am interested in how we remember the internet and our affective bonds to places on the web, and how that naturally conflicts with the web’s commercial infrastructure and subsequent dealings with “old data”.
Mackinnon, K. (2022), “Critical care for the early web: ethical digital methods for archived youth data,” Journal of Information, Communication and Ethics in Society
Mackinnon, K. (2022) “The death of GeoCities: seeking destruction and platform eulogies in Web archives,” Internet Histories, DOI: 10.1080/24701475.2022.2051331 (Open Access)
Shade, L, Henderson, M.J., and Mackinnon, K. (2021) “The past, present, and future of digital privacy for youth and children: Part 1 and 2.” Schwartz Reisman Institute for Technology and Society, University of Toronto. https://srinstitute.utoronto.ca/news/digital-privacy-youth-part-1
Mackinnon, K. (2021) “Dispatch: Ethical Challenges to Researching Youth Cultures in Historical Web Archives,” Studies in Social Justice,
Mackinnon, K., & Shade, L. R. (2020). “God Only Knows What It’s Doing to Our Children’s Brains”: A Closer Look at Internet Addiction Discourse. Jeunesse: Young People, Texts, Cultures, 12(1), 16-38.
I have been involved with a number of projects that engage with digital privacy and equity online, internet governance, youth media, technology history, and media history.
The eQuality Project (2015-2022)
Early Internet Memories
“The Algorithmic You”
Knowledge Media Design Institute (KMDI) – University of Toronto (2019)
Trans-Canada Computer Communication Network (TCCN) with Dr. Daniel Joseph
McLuhan Centre – University of Toronto (2019-2022)
Ursula Franklin Reading Group – edited essay collection
I am currently working on projects that engage with social media research ethics, platform archives, critical digital humanities, and participatory/collaborative research approaches to big data.