The purpose of the CASOS Summer Institute is to provide an intense and hands-on introduction to dynamic network analysis and computational modeling of complex socio-technical systems. Both network analysis and multi-agent modeling will be covered. Participants will be able to complete the institute without programming skills or in-depth understanding of particular social theories. Computer programming and basic social or organizational theory are not included under the topics covered.
Participants learn about current trends, practices, and tools available for social networks analysis, link analysis, simulation, and multi-agent modeling. Basic social network and dynamic network representations, statistics, analysis and visualization techniques are covered. Techniques for designing, analyzing, and validating computational models with and without network components are presented. There is also an emphasis on appropriate and inappropriate ways to critique computational models and network analyses. The strengths and weaknesses of computational and network approaches to examining complex socio-technical issues are discussed. Multiple computational platforms are explored and hands-on experience are provided. 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 students will learn and work with include: ORA, AutoMap, and Construct, which are network analysis, information extraction, and simulations tools, respectively, that are developed at CASOS and widely used globally in business, government, and education.
Students are encouraged to bring their own data and to learn to use the CASOS tools to code, analyze, reason about and visualize there data. Hands-on instruction and assistance will be provided on how to import data to ORA from CSV files, SQL databases, email servers, UCINET formats, PenLink, I2/Analyst Notebook and other raw data formats. Students will work through a tool chain where they extract networks from texts, analyze those networks, and the using simulation techniques evolve those networks.
The hands-on curriculum builds on both social network and computational analysis techniques, and illustrates how to use these techniques to study social, organizational and policy issues.
Examples are: email messages, webpage content, paper abstracts, news articles, comment fields from fixed formatted files.
Restrictions: Put one message, page, abstract, article per file.
Put all files for same group or time period in a folder. Exclude pictures.
Examples are: who talks to whom, trade level between countries, semantic networks, event networks.
Restrictions: Look at CASOS tools web page for easy formats to read. If you have node by attribute data, such as for each person degree, age, position you can use that data to create relational data.
Make sure your machine is large enough for your data. You can have multiple networks. Each network can be in its own file, but need not be. If you are bringing your own machine, which we highly recommend, just bring your data on your machine.