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

Frontiers in research metrics and analytics Pub Date : 2024-02-22 eCollection Date: 2024-01-01 DOI:10.3389/frma.2024.1335454
Yutong Cao, Nicole A Cheung, Dean Giustini, Jeffrey LeDue, Timothy H Murphy
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引用次数: 0

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.

Scholar Metrics Scraper (SMS):自动检索引文和作者数据。
学术部门、研究集群和评估人员分析作者和引用数据,以衡量研究影响并支持战略规划。我们创建了 Scholar Metrics Scraper (SMS),以自动检索一组研究人员的文献计量数据。该项目包含 Jupyter 笔记本,可将研究人员名单作为输入,并从谷歌学术(GS)中导出引文指标的 CSV 文件,从而直观地显示研究小组的影响力和合作情况。此外,还提供一系列图表输出。SMS 是自动检索和可视化引文数据的开放式解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.50
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0.00%
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审稿时长
14 weeks
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