Journal article mining: the scholarly publishers' perspective
Authors: Smit, Eefke; Van Der Graaf, Maurits
Source: Learned Publishing, Volume 25, Number 1, January 2012 , pp. 35-46(12)
Abstract:The essence of text mining and data mining is that a machine and software are used for content analysis of large digital corpora. The Publishing Research Consortium commissioned a study on content mining of scholarly journal articles with 29 expert interviews and an international survey among publishers. The main results are: (i) content mining developments appear to be accelerating with more applications in more areas; (ii) third-party demand for content mining is widespread but still at low levels of frequency; (iii) publishers' permissions for content mining are quite liberal, especially for research-driven mining requests; (iv) half of the publisher respondents undertake mining of their own content; and (v) content mining is on the rise – publishers and third parties both report an increase in planned mining activities. As content mining of journal articles spreads and intensifies, cross-publisher solutions can better help facilitate content mining. The study investigated the interest and willingness of publishers to support a set of different solutions, from one shared content mining platform to commonly agreed access terms for mining and standardization of mining-friendly content formats.
Document Type: Research Article
Publication date: 2012-01-01
- Editor in Chief: Alan Singleton
North American Editor: Diane Scott-Lichter
Reviews Editor: Pippa Smart
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