A web app for ranking computer science departments according to their research output in selective venues.
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README.md

Computer Science Rankings

This ranking of top computer science schools is designed to identify institutions and faculty actively engaged in research across a number of areas of computer science. Unlike US News and World Report's approach, which is exclusively based on surveys, this ranking is entirely metrics-based. It measures the number of publications by faculty that have appeared at the most selective conferences in each area of computer science.

This approach is intended to be difficult to game, since publishing in such conferences is generally difficult: contrast this with other approaches like citation-based metrics, which have been repeatedly shown to be easy to manipulate. That said, incorporating citations in some form is a long-term goal.

See the FAQ for more details.


This repository contains all code and data used to build the computer science rankings website, hosted here: http://csrankings.org

Adding or modifying affiliations

Please read CONTRIBUTING.md for full details on how to contribute.

Trying it out at home

Because of GitHub size limits, to run this site, you will want to download the DBLP data by running make update-dblp (note that this will consume upwards of 19GiB of memory). To then rebuild the databases, just run make.

You will also need to install libxml2-utils (or whatever package includes xmllint on your distro), npm, typescript, python-lxml, and basex at a minimum via a command line like:

apt-get install libxml2-utils npm python-lxml basex; npm install -g typescript

Acknowledgements and other rankings

This site was developed primarily by and is maintained by Emery Berger. It incorporates extensive feedback from too many folks to mention here, including many contributors who have helped to add and maintain faculty affiliations, home pages, etc.

This site is partially based on code and data originally collected by Swarat Chaudhuri (Rice University). The original faculty affiliation dataset was constructed by Papoutsaki et al.; since then, it has been extensively cleaned and updated. A previous ranking also used DBLP and Brown's dataset for ranking theoretical computer science.

Contains information from DBLP.org which is made available under the ODC Attribution License.

License

CSRankings is covered by the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.