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Journal article mining: the scholarly publishers' perspective
Author(s) -
SMIT Eefke,
VAN DER GRAAF Maurits
Publication year - 2012
Publication title -
learned publishing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.06
H-Index - 34
eISSN - 1741-4857
pISSN - 0953-1513
DOI - 10.1087/20120106
Subject(s) - publishing , standardization , computer science , content (measure theory) , content analysis , digital content , world wide web , data science , library science , information retrieval , political science , sociology , social science , law , mathematical analysis , mathematics , operating system
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.