SACS Toolkit: E-Social Science from a Systems Perspective

I am presenting the following paper at the upcoming sociocybernetics conference this June in Urbino Italy.

This year's conference is all about e-science and web science. The title is 'MODERNITY 2.0': EMERGING SOCIAL MEDIA TECHNOLOGIES AND THEIR IMPACTS.

For those following this blog, you know that I include e-science and web science on my map of complexity, situating them as the two newest areas of complexity science research.

My paper explores how the new toolkit my colleague, Fred Hafferty, and I have developed for modeling complex social systems (called the SACS Toolkit) can be used to manage and analyze web-based data. In fact, one of the reasons we created our toolkit was to find ways to address the growing complexity of digital data.

Here is the abstract of our paper. I will post the paper later in June, 2009.

The SACS Toolkit provides researchers a new informatics-based ontology and methodology for managing and analyzing the massive, multi-dimensional databases regularly encountered on the web today. The SACS Toolkit does this by functioning as an intermediary between the web and researcher. Its intermediary function provides researchers several advantages. In terms of ontology, the SACS Toolkit: 1) provides a user-based filing system (social complexity theory) that help researchers organize and link multidimensional databases in a theoretically meaningful manner; 2) the filing system is also designed to form a complex system—to match the complexity of most web-based data. In terms of method, the SACS Toolkit: 1) provides a novel algorithm (assemblage) researchers can use to model complex systems with web data; 2) this algorithm works with any type of data; and 3) can be used with most methodological techniques (e.g., field research, statistics, etc), including the latest advances in agent-based modeling, network analysis, e-science and web science. In the current paper, we demonstrate the utility of the SACS Toolkit by applying it to a web-based community health science database we are currently studying. We begin with a review of the SACS Toolkit. Next, we explore the ontological and methodological challenges our database presented us—focusing on how the SACS Toolkit solved them. Fourth, we examine the model of community health we built, showing how the SACS Toolkit allowed us to make important advances in the current health sciences literature. We end inductively, suggesting how others may likewise use the SACS Toolkit.

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