Author credit-assignment schemas: A comparison and analysis

Jian Xu, Ying Ding, Min Song, Tamy Chambers

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Credit assignment to multiple authors of a publication is a challenging task owing to the conventions followed within different areas of research. In this study, we present a review of different author credit-assignment schemas, which are designed mainly based on author position and the total number of coauthors on the publication. We implemented, tested, and classified 15 author credit-assignment schemas into 3 types: linear, curve, and “other” assignment schemas. Further investigation and analysis revealed that most of the methods provide reasonable credit-assignment results, even though the credit-assignment distribution approaches are quite different among different types. The evaluation of each schema based on PubMed articles published in 2013 shows that there exist positive correlations among different schemas and that the similarity of credit-assignment distributions can be derived from the similar design principles that stress the number of coauthors or the author position, or consider both. We provide a summary about the features of each credit-assignment schema to facilitate the selection of the appropriate one, depending on the different conditions required to meet diverse needs.

Original languageEnglish
Pages (from-to)1973-1989
Number of pages17
JournalJournal of the Association for Information Science and Technology
Volume67
Issue number8
DOIs
Publication statusPublished - 2016 Aug 1

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences

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