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Related Experiment Video

Updated: May 18, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

Published on: August 29, 2025

Scholarometer: a social framework for analyzing impact across disciplines.

Jasleen Kaur¹, Diep Thi Hoang, Xiaoling Sun

¹Center for Complex Networks and Systems Research, School of Informatics & Computing, Indiana University, Bloomington, United States of America. jakaur@indiana.edu

|September 18, 2012

Summary

Scholarometer uses crowdsourced annotations to create reliable scholarly impact metrics across disciplines. This social framework enhances bibliometric analysis for authors and publications.

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Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

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Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning

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Published on: August 29, 2025

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases

Published on: October 24, 2019

Area of Science:

Bibliometrics
Scholarly Communication
Information Science

Background:

Quantitative metrics for scholarly impact rely on usage and annotation data.
Current annotation systems are proprietary, journal-focused, and manually curated, limiting their effectiveness.
A need exists for dynamic, crowdsourced annotation systems to track evolving research landscapes.

Purpose of the Study:

To propose a social framework using crowdsourced annotations for scholarly impact measurement.
To introduce Scholarometer, a system for computing citation-based impact measures and disciplinary metrics.
To enable a universal impact measure for comparing scholarly impact across disciplines.

Main Methods:

Developed a social framework leveraging crowdsourced annotations of scholars.
Implemented the Scholarometer system to compute citation-based impact and disciplinary metrics.
Utilized heuristics to manage noisy bibliographic and annotation data, enabling data sharing and visualization.

Main Results:

Demonstrated the success of the crowdsourcing approach through usage statistics of collected and shared data.
Successfully implemented a universal impact measure using Scholarometer's elicited disciplinary bibliometric indicators.
Showcased Scholarometer's ability to provide data sharing and interactive visualization services.

Conclusions:

The proposed crowdsourcing framework effectively addresses limitations of current annotation systems.
Scholarometer provides a viable method for computing disciplinary and universal scholarly impact metrics.
The system facilitates effective comparison of scholarly impact across diverse disciplinary boundaries.