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bioRxivScientific Communication & EducationPreprint

Scholar Metrics Scraper (SMS): automated retrieval of citation and author data

N. A. Cheung, D. Giustini, J. LeDue, T. H. Murphy

PDFDOI

Abstract

Academic departments, research clusters and evaluators analyze author and citation data to measure research impact and to support strategic planning. We created a tool, Scholar Metrics Scraper (SMS), to automate the retrieval of this bibliometric data for our research team. The project contains Jupyter notebooks (publicly-shared here) that take a list of researchers as an input to export a CSV file of citation metrics from Google Scholar and figures to visualize the groups impact. SMS is a scalable, open and publicly-accessible solution for automating the retrieval of citation data over time for a group of researchers.

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