Andrea Wiggins

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Andrea Wiggins' ResearchMy research interests are in the area of computer-supported cooperative work (CSCW), and center on sociotechnical studies of work, examining the interaction of organizational settings, task design, and technology use. In particular, I am interested in social computing and public participation in scientific research, which intersect in virtual citizen science.

My research includes studies on citizen science, free/libre open source software development, and the iSchool community.

Citizen science is a type of scientific research in which professional researchers collaborate with members of the public. Our NSF-funded VOSS grant project involves developing a typology of citizen science projects as virtual organizations. Understanding how these projects create scientific knowledge is the focus of my dissertation research.

Free/libre open source software development is the phenomenon studied by the FLOSS research group at the iSchool at Syracuse University. My research includes studies of the dynamics of social network structures, classification of project success, and measure development. I have also worked on replicating prior FLOSS studies using analysis workflows to demonstrate the value of eScience approaches for social science research.

The iSchools are an interdisciplinary group of schools of information. Since 2005, the iSchools Caucus has been bringing together this growing community; my research in this area has examined the faculty compositions of these schools for evidence of intellectual diversity and institutional relationships.

A few other things that are interesting enough to share:

  • I had a lot of fun writing personas and scenarios for group projects in SI 622 and SI 682, courses on usability and interface design at the University of Michigan School of Information.
  • Information and communicable diseases both spread through social networks. Try out my multi-agent simulation for a model of HIV & AIDS transmission in Axtell & Epstein’s SugarScape , implemented with Netlogo. Adjust the variables to see their effect on the disease transmission events.