Author:
Cao Yutong,Cheung Nicole A.,Giustini Dean,LeDue Jeffrey,Murphy Timothy H.
Abstract
Academic departments, research clusters and evaluators analyze author and citation data to measure research impact and to support strategic planning. We created Scholar Metrics Scraper (SMS) to automate the retrieval of bibliometric data for a group of researchers. The project contains Jupyter notebooks that take a list of researchers as an input and exports a CSV file of citation metrics from Google Scholar (GS) to visualize the group's impact and collaboration. A series of graph outputs are also available. SMS is an open solution for automating the retrieval and visualization of citation data.
Funder
University of British Columbia
Canadian Institutes of Health Research
Natural Sciences and Engineering Research Council of Canada