Computing in Political Science
Research in political science has become increasingly computationally intensive. From data collection and processing (web scraping, GIS, text analysis, computer vision, big data) to numerical analysis of formal models to empirical methods (lab and online experiments, Monte Carlo studies, causal inference, machine learning, structural estimation), political scientists often require state-of-the-art computing resources. The Department of Political Science is privileged to have the following at its disposal.
Detailed information about university-wide IT resources (including VPN, web hosting, and computer labs) can be found here. Licensed software available to graduate students includes ArcGIS, Mathematica, Matlab, and SAS.
Faculty and graduate students in the Department of Political Science have sponsored access to BlueHive, the University's high-performance Linux cluster. In addition, department users have priority over two dedicated BlueHive nodes: bhd0042 (24 cores @ 3.2GHz with 278 GB memory) and bhd0043 (40 cores @ 2.4GHz with 371GB memory).
To obtain a BlueHive account, please email the department computing supervisor: Professor Sergio Montero. If you already have an account, this tutorial provides general information about BlueHive, tips on getting started, and department ground rules.
BlueHive users have a wealth of software at their disposal, including Gambit, Git and Git LFS, Jupyter, Julia, Knitro, Mathematica, Matlab, RStudio, Stata, Python, and numerous programming tools. Guidance on how to access specialized software running on BlueHive can be found here.
Tutorials and Documentation
Below are several tutorials and helpful resources that department faculty and graduate students have contributed over the years.
- Brief Introduction to LaTeX
- An Introduction to LaTeX Using Scientific Word
- Brief Introduction to R
- BlueHive Tutorial
- BlueHive Software