Author Credit for Transdisciplinary Collaboration
Author(s) -
Jian Xu,
Ying Ding,
Vincent Malic
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0137968
Subject(s) - index (typography) , computer science , set (abstract data type) , domain (mathematical analysis) , process (computing) , key (lock) , data science , knowledge management , actuarial science , management science , economics , mathematics , world wide web , mathematical analysis , computer security , programming language , operating system
Transdisciplinary collaboration is the key for innovation. An evaluation mechanism is necessary to ensure that academic credit for this costly process can be allocated fairly among coauthors. This paper proposes a set of quantitative measures (e.g., t_credit and t_index) to reflect authors’ transdisciplinary contributions to publications. These measures are based on paper-topic probability distributions and author-topic probability distributions. We conduct an empirical analysis of the information retrieval domain which demonstrates that these measures effectively improve the results of harmonic_credit and h_index measures by taking into account the transdisciplinary contributions of authors. The definitions of t_credit and t_index provide a fair and effective way for research organizations to assign credit to authors of transdisciplinary publications.
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