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Can you talk about what software packages, perhaps data structures and algorithms you use? Any shortcomings / low hanging fruit? I see the domain as an invaluable tool for a few applications... any particularly strong ones you can see?



The important thing here is the objective : there are different methods and tools to reach that objective.

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.


Wrt to algorithms / techniques used, you might want to check out this textbook by some of the Cornell folks:

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-...


Coursera offers about a half dozen courses in subjects seemingly related to CompSoc:

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


To play with some ideas, nothing is more accessible than NetLogo: https://ccl.northwestern.edu/netlogo/




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