The dates for the 2018 CASOS Summer Institute will be June 10th through 16th at the Gates/Hillman Complex at Carnegie Mellon University. Registration information can be found at 2018 Summer Institute Page.
Registration is now open!
CASOS Summer Institute
The CASOS Summer Institute is a week long event that provides an intense hands-on introduction to network analysis and visualization from a combined social-network, network-science, link-analysis and dynamic network analysis perspective. Social network, high-dimensional networks, semantic networks, and meta-networks are covered as are network dynamics and geo-spatial networks.
Participants learn about current trends, practices, and tools available for analyzing complex systems as networks. Basic social network and dynamic network measure for one-mode, bi-partite and multi-mode data are covered. Network statistic, analysis and visualization techniques are covered for static and dynamic networks. Techniques for extracting networks from text and social media are covered. Simulation techniques for forecasting change in these networks and their impact on the diffusion of ideas and beliefs are covered. Key issues associated with social media analytics, and big data are covered. Participants gain experience through a series of hands-on exercises. Data sets are provided for these exercises; however, participants who wish to can bring their own data and use it in these exercises. An examination of social network methods, complexity theory and procedures for integrating network-based metrics and statistics into computational models completes the program.
The software tools participants will learn and work with include: ORA-PRO, AutoMap, NetMapper, and Construct, which are network analysis & visualization, information extraction/text mining, and simulations tools, respectively, that are developed at CASOS and widely used globally in business, government, and education.
All participants will be given trial software, and a deep discount on the professional versions of the tools.
