Exploring the bibliometric and semantic nature of negative results

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• 作者：Christian Gumpenberger (1)
  Juan Gorraiz (1)
  Martin Wieland (1)
  Ivana Roche (2)
  Edgar Schiebel (3)
  Dominique Besagni (2)
  Claire Fran?ois (2)
  
• 关键词：Bibliometrics ; Scientometrics ; Negative result publication ; S&T information ; Semantic analysis ; Publication bias
• 刊名：Scientometrics
• 出版年：2013
• 出版时间：April 2013
• 年：2013
• 卷：95
• 期：1
• 页码：277-297
• 全文大小：642KB
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• 作者单位：Christian Gumpenberger (1)
  Juan Gorraiz (1)
  Martin Wieland (1)
  Ivana Roche (2)
  Edgar Schiebel (3)
  Dominique Besagni (2)
  Claire Fran?ois (2)
  
  1. Library and Archive Services, Bibliometrics Department, University of Vienna, Boltzmanngasse 5, 1090, Vienna, Austria
  2. INIST–CNRS Institut de l’Information Scientifique et Technique, 2 allée du Parc de Brabois, CS 10310, 54519, Vandoeuvre-les-Nancy Cedex, France
  3. AIT Austrian Institute of Technology GmbH, Tech Gate Vienna, Donau-City-Stra?e 1, 1220, Vienna, Austria
  
• ISSN：1588-2861

文摘

Negative results are not popular to disseminate. However, their publication would help to save resources and foster scientific communication. This study analysed the bibliometric and semantic nature of negative results publications. The Journal of Negative Results in Biomedicine (JNRBM) was used as a role model. Its complete articles from 2002-009 were extracted from SCOPUS and supplemented by related records. Complementary negative results records were retrieved from Web of Science in “Biochemistry-and “Telecommunications- Applied bibliometrics comprised of co-author and co-affiliation analysis and a citation impact profile. Bibliometrics showed that authorship is widely spread. A specific community for the publication of negative results in devoted literature is non-existent. Neither co-author nor co-affiliation analysis indicated strong interconnectivities. JNRBM articles are cited by a broad spectrum of journals rather than by specific titles. Devoted negative results journals like JNRBM have a rather low impact measured by the number of received citations. On the other hand, only one-third of the publications remain uncited, corroborating their importance for the scientific community. The semantic analysis relies on negative expressions manually identified in JNRBM article titles and abstracts and extracted to syntactic patterns. By using a Natural Language Processing tool these patterns are then employed to detect their occurrences in the multidisciplinary bibliographical database PASCAL. The translation of manually identified negation patterns to syntactic patterns and their application to multidisciplinary bibliographic databases (PASCAL, Web of Science) proved to be a successful method to retrieve even hidden negative results. There is proof that negative results are not only restricted to the biomedical domain. Interestingly a high percentage of the so far identified negative results papers were funded and therefore needed to be published. Thus policies that explicitly encourage or even mandate the publication of negative results could probably bring about a shift in the current scientific communication behaviour.