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dc.contributor.authorKousha, Kayvan
dc.contributor.authorThelwall, Mike
dc.date.accessioned2017-01-26T14:45:45Z
dc.date.available2017-01-26T14:45:45Z
dc.date.issued2015-09-23
dc.identifier.citationKousha, K., Thelwall, M. (2017) 'Patent citation analysis with Google' Journal of the Association for Information Science and Technology, 68 (1) p.48-61
dc.identifier.issn2330-1635
dc.identifier.doi10.1002/asi.23608
dc.identifier.urihttp://hdl.handle.net/2436/620354
dc.descriptionThis is an accepted manuscript of an article published by Wiley-Blackwell in Journal of the Association for Information Science and Technology on 23/09/2015, available online: https://doi.org/10.1002/asi.23608 The accepted version of the publication may differ from the final published version.
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.
dc.formatapplication/pdf
dc.language.isoen
dc.publisherWiley-Blackwell
dc.relation.urlhttp://doi.wiley.com/10.1002/asi.23608
dc.subjectScientometrics
dc.subjectPatent Citations
dc.subjectPatent analysis
dc.subjectGoogle Patents
dc.titlePatent citation analysis with Google
dc.typeJournal article
dc.identifier.journalJournal of the Association for Information Science and Technology
dc.date.accepted2015-07-13
rioxxterms.versionAM
dc.source.volume68
dc.source.issue1
dc.source.beginpage48
dc.source.endpage61
refterms.dateFCD2020-06-08T12:32:11Z
refterms.versionFCDAM
refterms.dateFOA2018-08-20T13:56:15Z
html.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.


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