Web networks, stories, and data

An ego-network map for tibetanculture.org. This map shows hyperlink connections leading to and from one site within the Tibet Movement.

An ego-network map for tibetanculture.org. This map shows hyperlink connections leading to and from one site within the Tibet Movement.

As a graduate student and postdoc, I focused extensively on the intersection between technology, society, and culture. My dissertation, Storytelling and Networking on Tibet, investigated the relationship between strategic storytelling decisions and hyperlinking strategies used on Tibet Movement and Chinese Communist Party websites websites.

I have also published on the use of strategic storytelling and online social and technical controls in the New Media and Society article, “To ‘Come to a Correct Understanding of Buddhism:’ A Case Study on Spiritualizing Technology, Religious Authority, and the Boundaries of Orthodoxy and Identity in a Buddhist Web Forum.”

As a postdoc, I have also worked on projects about energy model data production and translation on AEC teams and the global digital divide.


Selected Works

The Internet and Activism

Osburn, Laura. Storytelling and networking on Tibet: Relationships between narratives, framing and networks within and between two oppositional issue networks. PhD. dissertation, University of Washington, 2014, ResearchWorks Archive (http://hdl.handle.net/1773/26453).

Busch, Laura. “Collaborating and contesting Buddhist protests: Networking Buddhist activists and debating religious narratives during the 2007 Monastic Protests in Burma.” International Communication Association, Chicago, IL, May 2009. 

Digital Divide

Howard, Phillip, Laura Busch and Penelope Sheets. “Comparing digital divides: Internet access and social inequality in Canada and the United States.” Canadian Journal of Communication 35, no. 1 (2010): 109-128.

Big Data

Neff, Gina, Anissa Tanweer, Brittany Fiore-Gartland, and Laura Osburn. “Critique and contribute: A practice-based framework for improving critical data studies and data science.” Big Data 5, no. 2 (2017): , 85-97.