Trackademia

Welcome to Trackademia

The idea behind Trackademia is to build on existing academic databases like Google Scholar and OpenAlex so that you can trust the data and use it for whatever you want. That comes down to two things.

More data, and more ways to use it. We aggregate publication data from every major source into a single dataset and add information pulled from faculty CVs. Then we let you slice it however you want: choose which sources to build from, write your own formulas, weight journals, adjust for department size.

More accurate, and honest about where it isn’t. We focus on a smaller set of schools so we can verify everything carefully. Faculty lists come from department websites rather than being inferred from publication records, so we know who should be in the data before we go looking. When we can’t find data on someone, we record the gap instead of dropping them. Every number comes with a coverage rate you can check against ground truth.

Everything in Trackademia is built from seven units. AI merges duplicate records across sources and tags each publication so these categories hold up:

  • Publication — citation counts, authors, journal, peer review status, and more
  • Publication group — versions of the same work combined into one entity, such as a working paper and the article it became
  • Academic
  • Department
  • University
  • Field
  • Journal

There are two modes. In Database mode you browse the underlying records and filter by any of the seven units. In Analytics mode you get graphs and comparisons, and you switch views to compare two departments, compare one department against the average of the others, or see them all at once. Tabs let you focus on a particular level of the data.

Trackademia

Every graph on this site

Publications

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work
  • Works published per year Lines over years
    • Measure: Total, Mean per academic, Median per academic
    • Calendar year or years since PhD
    • In each year or cumulative
  • Citations received per year Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
    • In each year or cumulative
  • Citation distribution Bars
    • Value: Citations, Weighted citations
  • Citations by age of work Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per work, Median per work
  • Publication type mix Ranked bars
    • Value: Citations, Weighted citations, Publications
  • Top venues Ranked bars
    • Value: Citations, Weighted citations, Publications

Academics

Departmentshere

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic, Formula
  • Publications over time Lines over years
    • Measure: Total, Mean per academic, Median per academic, Formula
    • Calendar year or years since PhD
    • In each year or cumulative
  • Citations over time Lines over years
    • Value: Citations, Weighted citations
    • Measure: Total, Mean per academic, Median per academic, Formula
    • In each year or cumulative
  • Makeup by tenure track Stacked bars
  • Output by rank Grouped bars
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic, Formula
  • Academics ranked against academics Grouped bars
    • Value: Citations, Weighted citations, Publications
    • How many ranks (opens on 5)
  • Years to promotion Grouped bars
  • Journals used Stacked bars
    • Value: Citations, Weighted citations, Publications

Journals

Fields

  • Ranking Ranked table
    • Value: Citations, Weighted citations, Publications
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
  • Departments by field Bars
    • Measure: Total, Mean per work, Median per work, Mean per academic, Median per academic
  • University rollup Ranked bars
  • Coverage by field Ranked bars

Trackademia

Search the whole site

Search a person, a department, a journal or the title of a work. A person’s name brings up their profile, their publications, their department and the journals they publish in.
Trackademia
Value Measure

Departments

Citations by mean * log(1 + people)
1 Harvard Government 6 academics 175.1
2 Penn Political Science 4 academics 98.2
3 Yale Political Science 8 academics 97.1
4 Brown Political Science 3 academics 77.6
5 Cornell Government 4 academics 56.3
6 Princeton Politics 9 academics 47.6
7 Dartmouth Government 0 academics —
8 Columbia Political Science 5 academics —

560 citations over 37 of 55 works (67% carry a count). 13 of 39 academics have at least one counted work. A work with no citation count is unknown here, never a zero.

Publications over time

Works published in each year
Measure X axis

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Every selected work, by the year it was published. An undated work is in no year.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 2 0/2 0.0%
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 4 4/4 1.0%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 25 18/25 0.72%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 5 3/5 0.6%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 8 7/8 0.875%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 3 2/3 0.6666666666666666%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 8 3/8 0.375%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Citations over time

Citations received in each year
Value Measure

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Citations received in each year by the works these filters select.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 2 0/2 0.0%
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 4 4/4 1.0%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 25 18/25 0.72%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 5 3/5 0.6%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 8 7/8 0.875%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 3 2/3 0.6666666666666666%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 8 3/8 0.375%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Makeup by tenure track

Academics on and off the tenure track
Series: Other.0246810Harvard Other 66Yale Other 88Princeton Other 99Columbia Other 55Cornell Other 44Penn Other 44Brown Other 33HarvardYalePrincetonColumbiaCornellPennBrownAcademicsDepartment

Every academic the filters keep, by whether their current rank is on the tenure track (docs/definitions.md section 7). A rank in neither group - emeritus, postdoc, or a rank no CV states - is its own segment rather than filed under one of them: an emeritus professor was on the tenure track, and an unknown rank is not a claim about tenure at all.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 2 0/2 0.0%
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 4 4/4 1.0%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 25 18/25 0.72%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 5 3/5 0.6%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 8 7/8 0.875%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 3 2/3 0.6666666666666666%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 8 3/8 0.375%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Output by rank

Citations by mean * log(1 + people) at each rank
Value Measure
Series: Harvard Government, Yale Political Science, Princeton Politics, Columbia Political Science, Cornell Government, Penn Political Science, Brown Political Science.0.025.050.075.0Unknown Harvard Government over 6 academics 29.229.2Unknown Yale Political Science over 7 academics 62.762.7Unknown Princeton Politics over 9 academics 15.915.9Unknown Columbia Political Science over 5 academics 0.00.0Unknown Cornell Government over 4 academics 28.228.2Unknown Penn Political Science over 3 academics 0.00.0Unknown Brown Political Science over 3 academics 25.925.9Other Yale Political Science over 1 academics 6.96.9Other Penn Political Science over 1 academics 42.342.3UnknownOtherCitations by mean * log(1 + people)Rank

Harvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Each rank read on its own, so a department of thirty and one of sixty are comparable at the same career stage.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 2 0/2 0.0%
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 4 4/4 1.0%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 25 18/25 0.72%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 5 3/5 0.6%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 8 7/8 0.875%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 3 2/3 0.6666666666666666%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 8 3/8 0.375%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Academics ranked against academics

Each department's rank-n academic, citations
Value Ranks
Series: Dartmouth Government, Harvard Government, Yale Political Science, Princeton Politics, Columbia Political Science, Cornell Government, Penn Political Science, Brown Political Science.0501001502001 Harvard Government Katrina Forrester 90901 Yale Political Science Melody Huang 1561561 Princeton Politics Robert P. George 43431 Columbia Political Science Caterina Chiopris 001 Cornell Government Begüm Adalet 69691 Penn Political Science John S. Lapinski 61611 Brown Political Science Juliet Hooker 56562 Harvard Government Eric Beerbohm 002 Yale Political Science Isabela Mares 32322 Princeton Politics Alan Patten 16162 Columbia Political Science Daniel Luban 002 Cornell Government Christopher Robert Way 112 Penn Political Science Andrew Thompson 002 Brown Political Science Deva Woodly 003 Harvard Government Hojung Joo 003 Yale Political Science Jamie Hintson 17173 Princeton Politics Paul Frymer 333 Columbia Political Science Joshua Foa Dienstag 003 Cornell Government Alexandra Blackman 003 Penn Political Science John DiIulio 003 Brown Political Science Marion E. Orr 004 Harvard Government Michael Sandel 004 Yale Political Science Dimitrios Halikias 10104 Princeton Politics Gary Bass 004 Columbia Political Science Karuna Mantena 004 Cornell Government Kennia Coronado 004 Penn Political Science Marie Gottschalk 005 Harvard Government Shterna S. Friedman 005 Yale Political Science Lucia Rubinelli 665 Princeton Politics Jacob N. Shapiro 005 Columbia Political Science Mahmood Mamdani 0012345CitationsRank

Dartmouth GovernmentHarvard GovernmentYale Political SciencePrinceton PoliticsColumbia Political ScienceCornell GovernmentPenn Political ScienceBrown Political Science

Rank 5 of 9 at the deepest; 4 of 8 departments still have somebody at the last rank drawn. Rank n of one department is not otherwise related to rank n of another - what this compares is the shape of the lists.

What these filters select, per academic not what the graph divided by
Academic Academics CVScholarOpenAlex Works With a count
Alexandra Blackman 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Andrew Thompson 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Caterina Chiopris 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Daniel Luban 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Deva Woodly 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Eric Beerbohm 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Gary Bass 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Giulia Oskian 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Hojung Joo 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Jacob N. Shapiro 1 1/1 1.0% 0/1 0.0% 0/1 0.0% 0 —
Jan-Werner Müller 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
John DiIulio 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Jordan Rudinsky 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Karuna Mantena 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Kennia Coronado 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Mahmood Mamdani 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Marie Gottschalk 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Marion E. Orr 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Michael Sandel 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Nazmul Sultan 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Rory Truex duplicate-check placeholder 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Shterna S. Friedman 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Steven Smith 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Timothy Colton 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Yunhyae Kim 1 0/1 0.0% 0/1 0.0% 0/1 0.0% 0 —
Joshua Foa Dienstag 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 2 0/2 0.0%
Alan Patten 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 1 1/1 1.0%
Begüm Adalet 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 7 6/7 0.8571428571428571%
Christopher Robert Way 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 1 1/1 1.0%
Dimitrios Halikias 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 7 5/7 0.7142857142857143%
Isabela Mares 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 5 4/5 0.8%
Jamie Hintson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 2 2/2 1.0%
John S. Lapinski 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
Juliet Hooker 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 8 3/8 0.375%
Katrina Forrester 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 5 3/5 0.6%
Lucia Rubinelli 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 4 1/4 0.25%
Melody Huang 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 7 6/7 0.8571428571428571%
Paul Frymer 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 2 2/2 1.0%
Robert P. George 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 1 1/1 1.0%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.

Journals used

Where these departments place work, by works
Value
Series: value.American Political Science ReviewAmerican Political Science Review 44The Review of PoliticsThe Review of Politics 44The Annals of Applied StatisticsThe Annals of Applied Statistics 22Political TheoryPolitical Theory 22American Journal of Political ScienceAmerican Journal of Political Science 22Comparative Political StudiesComparative Political Studies 22PolityPolity 22Proceedings of the National Academy of SciencesProceedings of the National Academy of Sciences 11Political AnalysisPolitical Analysis 11PNAS NexusPNAS Nexus 11Election Law Journal Rules Politics and PolicyElection Law Journal Rules Politics and Policy 11EpidemiologyEpidemiology 11Harvard Data Science ReviewHarvard Data Science Review 11Modern Intellectual HistoryModern Intellectual History 11Political Science Research and MethodsPolitical Science Research and Methods 1101234JournalWorks

The twelve venues highest on this reading, of 35.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 2 0/2 0.0%
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 4 4/4 1.0%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 25 18/25 0.72%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 5 3/5 0.6%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 8 7/8 0.875%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 3 2/3 0.6666666666666666%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 8 3/8 0.375%
  • Over the academics these filters select, so a filtered page describes the academics it selected and not the whole department.
  • A row with nothing held draws no mark above: the graph is quiet there because the evidence is missing, not because the work is.
  • What there was to draw from, not what the graph divided by - the graph states its own denominator above.
  • A Scholar profile is attached when at least 3 of the CV titles are found on it, or 30% of them are; one at another institution or under a different name needs 10 titles, and a profile far larger than the CV that holds only a small part of it is refused. Its articles are then checked one by one: what is not a work, or not by this person, is not counted.