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

Autor: Yutong Cao, Nicole A. Cheung, Dean Giustini, Jeffrey LeDue, Timothy H. Murphy
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Frontiers in Research Metrics and Analytics, Vol 9 (2024)
Druh dokumentu: article
ISSN: 2504-0537
DOI: 10.3389/frma.2024.1335454
Popis: 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.
Databáze: Directory of Open Access Journals