Andrea Wiggins

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Andrea Wiggins' ResearchMy research interests include the social dynamics of collaboration, open movements, virtual teams, and self-organizing systems. My research interests, projects, and papers demonstrate my approaches to this broad area of inquiry. I have an Erdös number of 6.*

My primary research interest currently lies in understanding the processes involved in open knowledge generation. Open knowledge refers to data, content, and information that is free for unrestricted use, reuse, and distribution. I am interested in developing a better understanding of the coordination mechanisms that enable open knowledge creation, and the characteristics of open knowledge environments that support participation.

In general, I enjoy applying computational and quantitative analysis methods to large data sets, such as archives of secondary data. To investigate larger trends in sociotechnical systems, I apply social network analysis and data visualization methods, using tools like Taverna Workbench to create self-documenting, replicable analysis workflows that I can share with other researchers.

My research projects include studies on free/libre open source software development and social networks.

Free/libre open source software development is the phenomenon studied by the FLOSS research group at the iSchool at Syracuse University. Among our many recent efforts, I am investigating the social dynamics of self-organizing FLOSS development teams. I'm also working on replicating some prior FLOSS studies using analysis workflows to demonstrate the value of eResearch approaches to social science research in this area.

Social networks are an increasingly popular topic of study. My interests in network science lie in dynamic network analysis and complex adaptive systems; I've been fascinated by graphing relationships ever since taking graph theory as a math undergrad.

Full network visualization for the i-School network The full i-School network comprises 152 nodes and 429 edges, summarizing the 674 PhD degrees held by full-time faculty members of the 19 members of the iSchool Caucus as of January 2007.

Computer Science PhD networkThis network visualization is a comparison data set of the faculty of 29 top computer science departments in North America.  With 123 nodes, the set has 572 edges and summarizes 1121 PhDs in computer science.
  • 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 new window, implemented with Netlogo. Adjust the variables to see their effect on the disease transmission events.
  • An adaptive systems approach to evolving algorithms for geographical search in networks would allow parallel testing of many diverse algorithms on graphs with many different characteristics.  My EECS 594 research proposal, Adaptive Geographical Search in Networks [0.2 MB PDF] is a short overview of this approach.

Papers and Presentations

*Paul Erdös -> Michael S. O. Molloy -> Cristopher Moore -> James P. Crutchfield -> Bernardo A. Huberman -> Lada A. Adamic -> me

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