Tutorial 7: Network and Topical Analysis for the Humanities using NWB and Sci2

Half-day tutorial
Time: Sunday, June 19, 1:00 – 4:30 p.m.
Room: Meyer Library 280E (Language Lab)

Scott Weingart, Katy Börner, Russell Duhon, Micah Linnemeier, Patrick Phillips, Joseph Biberstine, Chintan Tank, Chin Hua Kong

Topics: databases & dbms, geographic information systems / mapping, text analysis, other
Keywords: network analysis, data manipulation, bibliometrics

More and more, research in the humanities requires making use and sense of datasets that represent the structure and dynamics of complex natural and man-made systems. Recent trends in the digital humanities have resulted in the wide-scale availability of this data. The analysis, navigation, and management of these large-scale, dynamically changing datasets requires a new kind of tool, a macroscope (from macro, great, and skopein, to observe).

Microscopes empowered our naked eyes to see cells, microbes, and viruses, thereby advancing the progress of biology and medicine. Telescopes opened our minds to the immensity of the cosmos and prepared mankind for the conquest of space. Macroscopes promise to help us cope with another infinite: the infinitely complex. They allow us to detect patterns, trends, and outliers, give access to details, present a ‘vision of the whole,’ and assist our ‘synthesis’ of what we observe. While most microscopes and telescopes are static physical instruments, macroscopes are continuously changing bundles of software deployed as cyberinfrastructures, Web services, or standalone tools.

This tutorial presents and demonstrates CIShell powered tools such as the Science of Science (Sci2) Tool (http://sci.slis.indiana.edu/sci2) and the Network Workbench (NWB) Tool (http://nwb.slis.indiana.edu). The NWB Tools is a network analysis, modeling, and visualization toolkit for physics, biomedical, social science, and other multidisciplinary research. The Sci2 Tool was specifically designed for researchers and science policy makers interested to study and understand the structure and dynamics of science. Both tools are standalone desktop applications that install and run on Windows, Linux x86 and Mac OSX. The tools provide easy access to more than 180 algorithms and diverse sample datasets for the study of networks, as well as the loading, processing, and saving of 20 file formats (e.g., GraphML, Pajek .net, XGMML, and NWB) and an automatic conversion service among those supported formats. Then tools will be utilized for the analysis of temporal, geospatial, topical, and network datasets, and the professional visualization of analysis results by means of large-format charts and maps.

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