I'm quite happy to see this on HN. Like many other disciplines, our field is blossoming with the rise of cheap, high performance computing!
If your involved in this field and on HN, please reach out to me at @generativist on twitter. I'm in the process of setting up a community for CSS work, and will be soliciting feedback soon!
Can you give more details (accessible to programmers rather than social scientists) how that'd work, what do you actually model and aim to find out? Sounds pretty interesting.
Also, my entire dissertation is Python/Cython/Jupyter with a prebuilt docker container, so, it's also low-friction to play with. But, complicated by dissertation rules for sharing pre-publication (i.e. "is this definitely your work, because it's on github and you accepted PRs?").
http://www.cs.cornell.edu/home/kleinber/networks-book/
They also made an EdX course for it:
https://www.edx.org/course/networks-crowds-markets-cornellx-...
Social and Economic Networks: Models and Analysis, Stanford
Networks: Friends, Money, and Bytes, Princeton
Sampling People, Networks and Records, Michigan
Applied Social Network Analysis in Python, Michigan
Capstone: Analyzing (Social) Network Data, UCSD
Social Computing, UCSD
Measuring Causal Effect in the Social Sciences, U Copenhagen
Smart Cities, EPFL
Organizational Analysis, Stanford
Primarily, the objective of Computational Social Science is to understand human behavior but with computational methods. Traditionally, social science was done offline with surveys. But, with the increase in social information on the Internet could we use that data to know more about humans?
How? There are various methods on how one could do so - network theory, statistics, text mining etc. are some tools that are useful to achieve the objective.