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
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Journal

Vaccine

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Citation weight

Tierunranked
Weight in force1×
Weightingoff

Weight inputs

Each figure with its percentile among the ranked journals. A is the median, over the academics with a work here, of that academic’s citations to the works this site counts for them - never a Google Scholar profile total. Over every academic of this field, all years, whatever the filters select.

A · academics’ median13,980.5 · —
B · citations per work133.3 · —
N · works12 · —
P · academics8 · —
Formula result—
Below the thresholdfewer than 20 works: unranked, and weighs 1

From this institution

Under these filters. A work with no citation count is unknown here, never a zero.

Works5
Citations86 over 4 of 5 works
Citations per counted work21.5
Weighted citations—
Academics4
Departments2
First seen2022

Works placed per year

5 of these 5 works carry a year; an undated work is in no year. Works placed, under these filters.

Departments publishing there 2

DepartmentWorks
Cornell Government4
Yale Political Science1

A work held by two departments counts once in each, so these add up to more than the works above.

Works placed there 5

YearTitleAcademicsCitations
2022The correlates and dynamics of COVID-19 vaccine-specific hesitancyPeter John Loewen46
2022How do COVID-19 vaccine mandates affect attitudes toward the vaccine and participation in mandate-affected activities? Evidence from the United StatesDouglas L. Kriner · Sarah E. Kreps22
2023Personal risk or societal benefit? Investigating adults' support for COVID-19 childhood vaccinationGregory Alain Huber14
2023Persistent Drop in Confidence Following US Recommended Pause of Ad26.COV2.S VaccineDouglas L. Kriner4
2022The correlates and intensity of COVID-19 vaccine brand preferences.Peter John Loewen—

Citations as counted, before any journal weight: 4 of these 5 works carry a count, and a work with no count is unknown, never a zero.