Patent citation analysis with G oogle

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. G oogle 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 B ing to extract and filter patent citations from G oogle to academic papers with an overall precision of 98%. The method was evaluated with 322,192 science and engineering S copus articles from every second year for the period 1996–2012. Although manual G oogle Patent searches give more results, especially for articles with many patent citations, the difference is not large enough to be a major problem. Within B iomedical E ngineering, B iotechnology, and P harmacology & P harmaceutics, 7% to 10% of S copus 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 G oogle Patent citations and S copus citations across all fields suggest that traditional citation counts cannot substitute for patent citations when evaluating research.