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<!DOCTYPE HTML PUBLIC "-//IETF//DTD HTML//EN">
<html>
<head>
<link href='https://fonts.googleapis.com/css?family=News+Cycle:400,700' rel='stylesheet' type='text/css'>
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<meta name="description" content="Computer Science Rankings">
<meta name="keywords" content="computer science rankings, best computer science programs, best computer science schools, top computer science schools, top computer science universities, best computer science programs">
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<title>FAQ - CSRankings: Computer Science Rankings (beta)</title>
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<div class="container">
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<h1>FAQ Computer Science Rankings (beta)</h1>
<div class="panel panel-info">
<div class="panel-heading">
<p>
Frequently asked questions for <a href="http://csrankings.org">CSRankings.org</a>.
</p>
<div class="row">
<!-- col-xs-3 col-sm-6 col-md-4 -->
<div class="col-sm-12 col-md-12 col-lg-12">
<div class="table">
<table class="table-sm table-striped">
<thead>
<tr>
<th>
<p><br />Why another ranking? Why this methodology?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
Rankings are intensely popular and
influential. While we might wish for a
world without rankings, wishing will not
make rankings go away.
</p>
<p>Given this state of affairs, it makes
sense to aim for a ranking system that
is meaningful and transparent. Unfortunately, the most influential
rankings right now are those from US
News and World Report, which is entirely
reputation-based and <a target="_blank"
href="http://www.usnews.com/education/best-graduate-schools/articles/science-schools-methodology">relies
on surveys sent to department heads and
directors of graduate studies.</a>
</p>
<p>
By contrast, CSRankings is entirely
metrics-based: it weighs departments by
their presence at the most prestigious
publication venues. This approach is
intended to be both incentive-aligned
(faculty already aim to publish at top
venues) and difficult to game, since
publishing in such conferences is
difficult. It is admittedly bean-counting,
but its intent is to "count the right
beans." It is also entirely transparent;
all code and data are publicly available
at <a href="https://github.com/emeryberger/CSRankings">
https://github.com/emeryberger/CSRankings
</a> under a <a rel="license"
href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative
Commons
Attribution-NonCommercial-NoDerivatives
4.0 International License</a> (note: this
means you may not distribute anything built from
CSrankings' code or data).
</p>
<p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />How about incorporating citations?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
Unfortunately, citation-based metrics have
been repeatedly shown to
be <a target="_blank"
href="http://arxiv.org/abs/1212.0638">subject</a>
to <a target="_blank"
href="http://evaluation.hypotheses.org/files/2010/12/pdf_IkeAntkareISSI.pdf">manipulation</a>. There
are <a href="http://retractionwatch.com/2017/08/22/one-way-boost-unis-ranking-ask-faculty-cite/">universities
instructing faculty</a> to cite each
other, and the phenomenon
of <a href="https://www.statnews.com/2017/01/13/citation-cartels-science/">"citation
cartels"</a> is well documented.
</p>
<p>There are also methodological challenges:
citations for all papers are not freely
available and change rapidly, and citation
count systems like Google Scholar do not do
a great job of disambiguating
authors <em>and</em> can be gamed by
authors. (See <a href="https://scholar.google.com/citations?user=qGuYgMsAAAAJ&hl=en">Et
al.'s</a> page for a humorous example.)
</p>
<p>Note that selective conferences are
already a proxy for citation impact:
papers published at these conferences are
on average much more highly cited than
papers that appear in less selective, less
prestigious venues.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />What do <em>adjusted counts</em> and <em>average counts</em> mean?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p><b>Adjusted counts</b>: each publication is counted
exactly once, with credit adjusted by splitting evenly
across all co-authors. This approach makes it impossible to
boost rankings simply by adding authors to a paper.
<b>Average count</b> computes the
geometric mean of the adjusted counts in
each area (+ 1) for each
institution. <em>This approach normalizes
for the size of areas, so that large and
small areas are weighed the same,
regardless of publication rate.</em>
</p>
<p>
Note that publications must be at least 6 pages long to be counted.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />
How were research areas determined?
<br />
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
Nearly all categories are based on
research-focused <a href="http://www.acm.org/special-interest-groups">ACM
SIGs</a>. Areas not represented by ACM
SIGs are intended to span <em>most</em>
established research-centric areas of
computer science.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />Why is (some area) not included?<br />
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
For any research-focused area to be
included, at least 50
<a href="https://en.wikipedia.org/wiki/List_of_research_universities_in_the_United_States#Universities_classified_as_.22R1:_Doctoral_Universities_-_Highest_Research_Activity.22">R1
institutions</a> must have publications in the
top conferences in that area in the last 10 years.
This threshold is to ensure that there is
enough research activity in an area to
enable a meaningful ranking. A number of ACM
SIGs do not meet this criteria.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />
How were the conferences selected?
<br />
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
The conferences listed were developed in consultation
with faculty across a range of
institutions, including via community surveys. These
are <a href="https://scholar.google.com/citations?view_op=top_venues&hl=en&vq=eng">the
most impactful</a> and selective
conferences for each area.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />Why so few conferences per area?<br />
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
Only the very top conferences in each area
are listed. All conferences listed must be
roughly equivalent in terms of number of
submissions, selectivity and impact to
avoid creating incentives to target less
selective conferences.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />Why is conference X not listed?<br />
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
Additional
conferences are not listed when they
are not roughly equivalent to the rest in
terms of number of submissions,
selectivity and citation impact.
</p>
<p>For example: in the area of programming
languages, PLDI and POPL
currently get roughly 300 and 220
submissions each year, respectively. Their
acceptance rates over the last 10 years
are 20% and 21%, while their
citation impacts (measured by h5-median,
via Google Scholar) are 69 and 65 (higher is better).
</p>
<p>For illustration, here are the stats for
other conferences in this area which did not make the cut:
<ul>
<li>OOPSLA: 200 submissions / year, 25% acceptance rate, h5-median: 49.</li>
<li>PPoPP: 150 submissions / year, 21% acceptance rate, h5-median: 50.</li>
<li>ICFP: 100 submissions / year, 31% acceptance rate, h5-median: 35.</li>
</ul>
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />How is authorship count adjusted?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
A single faculty member gets 1/N credit for a paper, where N is the
number of authors, regardless of their affiliation or status (faculty,
student, or otherwise). The number never changes. A paper can count
for at most 1.0, in the case that all authors are / end up becoming
faculty in the database.
</p>
<p>
The key downside to counting papers
without adjusting for authors is that it
would make it trivial to inflate the
effect of writing a single paper simply by
adding authors. Splitting authorship
credit means that authors are incentivized
to
appropriately <a href="http://www.acm.org/publications/policies/policy_on_authorship">treat
authorship credits</a>. Note that
publication rates are normalized across
areas.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />How about adjusting the count only by faculty in the database (or some other means)?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
Here are some of the
numerous downsides of only including
authors present in the database:
<ul>
<li>Authorship counts would be difficult
to calculate (manually).</li>
<li>Authorship counts would be dynamic
(that is, they would change over
time). When an author dies and is no
longer in the database, everyone else
would have to have their credit
increased (talk about perverse
incentives).</li>
<li>It would create an incentive
for senior faculty to have their junior
collaborators not get tenure (since they
would then likely leave the
database).</li>
<li>It would favor collaboration with
industry (not in the database) over
collaboration with academics. Note that
companies do not
generally provide public access to their
employee directories.</li>
<li>It would create a disincentive for
faculty to see their students get
faculty appointments (since it would
reduce credit).</li>
</ul>
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />What are the criteria for including faculty?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
The criteria for inclusion (which have
been refined since CSRankings' inception)
are that anyone who is a full-time,
tenure-track faculty member on a given
campus <em>who can advise PhD
students</em> in Computer Science can be
included in the database. This approach
thus extends the reach of the database to
a number of faculty from other departments
who have adjunct appointments with a CS
department or similar that let them advise
CS PhD students.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />What about including faculty from ECE, Informatics, etc.?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
As mentioned above, tenure-track faculty
who can advise PhD students in CS can be
included regardless of their home
department. The primary audience of
CSRankings is prospective graduate
students who are seeking a postgraduate
degree in Computer Science.
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />Why isn't <em>(prestigious science journal A)</em> included?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
CSrankings uses DBLP as its data source,
and DBLP does not currently index general
science journals (including Science, Nature,
and PNAS).
</p>
</td>
</tr>
</tbody>
<thead>
<tr>
<th>
<p><br />How can I submit change requests (to add faculty, change home pages, change affiliations, etc.)?
</p>
</th>
</tr>
</thead>
<tbody>
<tr>
<td>
<p>
There are two ways you can do this:
<ul>
<li>
<em>Preferred:</em> Issue a
pull request for
the <a href="https://github.com/emeryberger/CSRankings">GitHub
repo</a>. To add or modify a faculty
member's affiliation, update the
file <tt>faculty-affiliations.csv</tt>
and <tt>homepages.csv</tt>. If you are
adding a non-US institution, add
it to <tt>country-info.csv</tt>.
</li>
<li>
<em>Less preferred:</em> Use this Google Form to enter the additions or changes: <a href="http://goo.gl/forms/MDDMN0UKuCwkOyFT2">http://goo.gl/forms/MDDMN0UKuCwkOyFT2</a>.
</li>
</ul>
In either case, please make sure that the
faculty's name corresponds to
their <a href="http://dblp.uni-trier.de/search/">DBLP</a>
author entry. <b>Please
read <a href="https://github.com/emeryberger/CSrankings/blob/gh-pages/docs/CONTRIBUTING.md">this
guide to contributing</a> before
submitting any proposed changes.</b>
</p>
</td>
</tr>
</tbody>
</table>
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</div>
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