Abstract
Purpose: The purpose of this paper is to investigate the feasibility of automating Google Scholar searching to harvest citation data of monographs for collection analysis. Design/methodology/approach: This study discusses the creation and refinement of a Scraper application programming interface query structure created to match library collection inventories to their Google Scholar listings to retrieve citation counts. Findings: This paper indicates that Google Scholar is a feasible and usable tool for retrieving monograph citation data. Originality/value: This study shows that Google Scholar citation data can be harvested for monographs in an automated fashion to serve as a source of bibliographic data, something not typically done outside of individual academics and writers tracking their personal academic impact factors.
Original language | English (US) |
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Journal | Library Hi Tech News |
DOIs | |
State | Accepted/In press - 2023 |
All Science Journal Classification (ASJC) codes
- Information Systems
- Library and Information Sciences