Research power ranking: Adapting the Elo system to quantify scientist evaluation

This article presents an original model for assessing scientific productivity, research power ranking (RPR), which is based on the adaptation of the Elo-rating system to the context of scientific activity. Unlike traditional scientometric indicators, RPR accounts for the dynamics, multidimensionality, and relativity of research power. The model comprises three components—fundamental, applied, and commercial activity—each represented by a separate rating and updated on the basis of probabilistic “scientific games” analogous to chess matches. The scientific rating of each researcher is calculated as a weighted sum of the components, allowing the model to reflect not only their current position but also their career trajectory, including phase transitions, breakthroughs, and changes in scientific style. Numerical simulations were conducted for both the individual trajectories and population-level distributions of the researchers. Phase diagrams were constructed, and a typology of scientific styles was formulated. The results demonstrate that RPR can serve as a universal tool for objective assessment, strategic planning, and visualization of scientific reputation in both academic and applied environments.

Authors

Institutions

Publication Details

Journal
Journal of Information Science
Published
2026-04-21
DOI
https://doi.org/10.1177/01655515261437411
Primary Topic
scientometrics and bibliometrics research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Research power ranking: Adapting the Elo system to quantify scientist evaluation

Bisenbaev Ak
Journal of Information Science
scientometrics and bibliometrics research
article

Research power ranking: Adapting the Elo system to quantify scientist evaluation

Bisenbaev Ak
article en

Abstract

This article presents an original model for assessing scientific productivity, research power ranking (RPR), which is based on the adaptation of the Elo-rating system to the context of scientific activity. Unlike traditional scientometric indicators, RPR accounts for the dynamics, multidimensionality, and relativity of research power. The model comprises three components—fundamental, applied, and commercial activity—each represented by a separate rating and updated on the basis of probabilistic “scientific games” analogous to chess matches. The scientific rating of each researcher is calculated as a weighted sum of the components, allowing the model to reflect not only their current position but also their career trajectory, including phase transitions, breakthroughs, and changes in scientific style. Numerical simulations were conducted for both the individual trajectories and population-level distributions of the researchers. Phase diagrams were constructed, and a typology of scientific styles was formulated. The results demonstrate that RPR can serve as a universal tool for objective assessment, strategic planning, and visualization of scientific reputation in both academic and applied environments.

Journal of Information Science
Ministry of Education and Science of the Republic of Kazakhstan (KZ), Institute of Philosophy, Political Science and Religious Studies (KZ)
Ministry of Education and Science of the Republic of Kazakhstan
Decent work and economic growth
Openalex Percentile: Top 5%
scientometrics and bibliometrics research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.