2.50
Hdl Handle:
http://hdl.handle.net/2436/620354
Title:
Patent citation analysis with Google
Authors:
Kousha, Kayvan; Thelwall, Mike ( 0000-0001-6065-205X )
Abstract:
Citations from patents to scientific publications provide useful evidence about the commercial impact of academic research, but automatically searchable databases are needed to exploit this connection for large-scale patent citation evaluations. Google covers multiple different international patent office databases but does not index patent citations or allow automatic searches. In response, this article introduces a semiautomatic indirect method via Bing to extract and filter patent citations from Google to academic papers with an overall precision of 98%. The method was evaluated with 322,192 science and engineering Scopus articles from every second year for the period 1996–2012. Although manual Google Patent searches give more results, especially for articles with many patent citations, the difference is not large enough to be a major problem. Within Biomedical Engineering, Biotechnology, and Pharmacology & Pharmaceutics, 7% to 10% of Scopus articles had at least one patent citation but other fields had far fewer, so patent citation analysis is only relevant for a minority of publications. Low but positive correlations between Google Patent citations and Scopus citations across all fields suggest that traditional citation counts cannot substitute for patent citations when evaluating research.
Citation:
Patent citation analysis with Google 2017, 68 (1):48 Journal of the Association for Information Science and Technology
Publisher:
Wiley-Blackwell
Journal:
Journal of the Association for Information Science and Technology
Issue Date:
Jan-2017
URI:
http://hdl.handle.net/2436/620354
DOI:
10.1002/asi.23608
Additional Links:
http://doi.wiley.com/10.1002/asi.23608
Type:
Article
ISSN:
23301635
Appears in Collections:
Statistical Cybermetrics Research Group

Full metadata record

DC FieldValue Language
dc.contributor.authorKousha, Kayvanen
dc.contributor.authorThelwall, Mikeen
dc.date.accessioned2017-01-26T14:45:45Z-
dc.date.available2017-01-26T14:45:45Z-
dc.date.issued2017-01-
dc.identifier.citationPatent citation analysis with Google 2017, 68 (1):48 Journal of the Association for Information Science and Technologyen
dc.identifier.issn23301635-
dc.identifier.doi10.1002/asi.23608-
dc.identifier.urihttp://hdl.handle.net/2436/620354-
dc.description.abstractCitations from patents to scientific publications provide useful evidence about the commercial impact of academic research, but automatically searchable databases are needed to exploit this connection for large-scale patent citation evaluations. Google covers multiple different international patent office databases but does not index patent citations or allow automatic searches. In response, this article introduces a semiautomatic indirect method via Bing to extract and filter patent citations from Google to academic papers with an overall precision of 98%. The method was evaluated with 322,192 science and engineering Scopus articles from every second year for the period 1996–2012. Although manual Google Patent searches give more results, especially for articles with many patent citations, the difference is not large enough to be a major problem. Within Biomedical Engineering, Biotechnology, and Pharmacology & Pharmaceutics, 7% to 10% of Scopus articles had at least one patent citation but other fields had far fewer, so patent citation analysis is only relevant for a minority of publications. Low but positive correlations between Google Patent citations and Scopus citations across all fields suggest that traditional citation counts cannot substitute for patent citations when evaluating research.en
dc.publisherWiley-Blackwellen
dc.relation.urlhttp://doi.wiley.com/10.1002/asi.23608en
dc.rightsArchived with thanks to Journal of the Association for Information Science and Technologyen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectScientometricsen
dc.subjectPatent Citationsen
dc.subjectPatent analysisen
dc.subjectGoogle Patentsen
dc.titlePatent citation analysis with Google-
dc.typeArticleen
dc.identifier.journalJournal of the Association for Information Science and Technologyen
dc.contributor.institutionStatistical Cybermetrics Research Group; School of Mathematics and Computer Science; University of Wolverhampton; Wulfruna Street Wolverhampton WV1 1LY UK-
dc.contributor.institutionStatistical Cybermetrics Research Group; School of Mathematics and Computer Science; University of Wolverhampton; Wulfruna Street Wolverhampton WV1 1LY UK-
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