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 1,204.5
2 Princeton Politics 9 academics 1,024.7
3 Brown Political Science 3 academics 912.2
4 Penn Political Science 4 academics 902.9
5 Yale Political Science 8 academics 499.6
6 Cornell Government 4 academics 213.3
7 Columbia Political Science 5 academics 64.5
8 Dartmouth Government 0 academics —

4,611 citations over 97 of 129 works (75% carry a count). 14 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 —
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 20 17/20 0.85%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 47 37/47 0.7872340425531915%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 12 9/12 0.75%
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 6 3/6 0.5%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 13 11/13 0.8461538461538461%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 6 5/6 0.8333333333333334%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 25 15/25 0.6%
  • 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 —
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 20 17/20 0.85%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 47 37/47 0.7872340425531915%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 12 9/12 0.75%
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 6 3/6 0.5%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 13 11/13 0.8461538461538461%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 6 5/6 0.8333333333333334%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 25 15/25 0.6%
  • 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 —
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 20 17/20 0.85%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 47 37/47 0.7872340425531915%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 12 9/12 0.75%
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 6 3/6 0.5%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 13 11/13 0.8461538461538461%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 6 5/6 0.8333333333333334%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 25 15/25 0.6%
  • 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.0.0100.0200.0300.0400.0Unknown Harvard Government over 6 academics 200.8200.8Unknown Yale Political Science over 7 academics 330.3330.3Unknown Princeton Politics over 9 academics 341.6341.6Unknown Columbia Political Science over 5 academics 12.912.9Unknown Cornell Government over 4 academics 106.6106.6Unknown Penn Political Science over 3 academics 0.00.0Unknown Brown Political Science over 3 academics 304.1304.1Other Yale Political Science over 1 academics 17.317.3Other Penn Political Science over 1 academics 388.9388.9UnknownOtherCitations 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 —
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 20 17/20 0.85%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 47 37/47 0.7872340425531915%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 12 9/12 0.75%
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 6 3/6 0.5%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 13 11/13 0.8461538461538461%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 6 5/6 0.8333333333333334%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 25 15/25 0.6%
  • 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.02505007501 Harvard Government Katrina Forrester 6196191 Yale Political Science Isabela Mares 6186181 Princeton Politics Robert P. George 6796791 Columbia Political Science Joshua Foa Dienstag 36361 Cornell Government Begüm Adalet 2582581 Penn Political Science John S. Lapinski 5615611 Brown Political Science Juliet Hooker 6586582 Harvard Government Eric Beerbohm 002 Yale Political Science Melody Huang 3133132 Princeton Politics Paul Frymer 5105102 Columbia Political Science Caterina Chiopris 002 Cornell Government Christopher Robert Way 772 Penn Political Science Andrew Thompson 002 Brown Political Science Deva Woodly 003 Harvard Government Hojung Joo 003 Yale Political Science Lucia Rubinelli 1641643 Princeton Politics Alan Patten 1461463 Columbia Political Science Daniel Luban 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 25254 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 Jamie Hintson 17175 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 —
Alan Patten 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 9 9/9 1.0%
Begüm Adalet 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 11 9/11 0.8181818181818182%
Christopher Robert Way 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 2 2/2 1.0%
Dimitrios Halikias 1 1/1 1.0% 1/1 1.0% 1/1 1.0% 9 7/9 0.7777777777777778%
Isabela Mares 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 16 14/16 0.875%
Jamie Hintson 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 3 2/3 0.6666666666666666%
John S. Lapinski 1 1/1 1.0% 0/1 0.0% 1/1 1.0% 6 5/6 0.8333333333333334%
Joshua Foa Dienstag 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 6 3/6 0.5%
Juliet Hooker 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 25 15/25 0.6%
Katrina Forrester 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 12 9/12 0.75%
Lucia Rubinelli 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 11 7/11 0.6363636363636364%
Melody Huang 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 8 7/8 0.875%
Paul Frymer 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 7 4/7 0.5714285714285714%
Robert P. George 1 0/1 0.0% 1/1 1.0% 0/1 0.0% 4 4/4 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.

Years to promotion

From the PhD to each rank
Series: Penn Political Science.0.05.010.015.020.0Full or distinguished Penn Political Science median of 1 academics 17.017.0Full or distinguishedYears since the PhDRank reached

The median years from the PhD year a CV states to the first year it states that rank. An academic whose CV dates neither is in neither figure.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 20 17/20 0.85%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 47 37/47 0.7872340425531915%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 12 9/12 0.75%
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 6 3/6 0.5%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 13 11/13 0.8461538461538461%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 6 5/6 0.8333333333333334%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 25 15/25 0.6%
  • 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.Political TheoryPolitical Theory 66Perspectives on PoliticsPerspectives on Politics 66The Review of PoliticsThe Review of Politics 55American Journal of Political ScienceAmerican Journal of Political Science 44Comparative Political StudiesComparative Political Studies 44South Atlantic QuarterlySouth Atlantic Quarterly 44American Political Science ReviewAmerican Political Science Review 44Contemporary Political TheoryContemporary Political Theory 44History of Political ThoughtHistory of Political Thought 33PolityPolity 33PS Political Science & PoliticsPS Political Science & Politics 33Political Science Research and MethodsPolitical Science Research and Methods 22Government and OppositionGovernment and Opposition 22The Annals of Applied StatisticsThe Annals of Applied Statistics 22History of European IdeasHistory of European Ideas 220123456JournalWorks

The twelve venues highest on this reading, of 57.

What these filters select, per department not what the graph divided by
Department Academics CVScholarOpenAlex Works With a count
Dartmouth Government 0 — — — 0 —
Princeton Politics 9 1/9 0.1111111111111111% 3/9 0.3333333333333333% 0/9 0.0% 20 17/20 0.85%
Yale Political Science 8 2/8 0.25% 4/8 0.5% 2/8 0.25% 47 37/47 0.7872340425531915%
Harvard Government 6 0/6 0.0% 1/6 0.16666666666666666% 0/6 0.0% 12 9/12 0.75%
Columbia Political Science 5 0/5 0.0% 1/5 0.2% 0/5 0.0% 6 3/6 0.5%
Cornell Government 4 0/4 0.0% 2/4 0.5% 0/4 0.0% 13 11/13 0.8461538461538461%
Penn Political Science 4 1/4 0.25% 0/4 0.0% 1/4 0.25% 6 5/6 0.8333333333333334%
Brown Political Science 3 0/3 0.0% 1/3 0.3333333333333333% 0/3 0.0% 25 15/25 0.6%
  • 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.