title: Author Credit for Transdisciplinary Collaboration.
abstract: 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.
authors.affiliation: School of Information Management, Sun Yat-sen University, Guangzhou, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Xu
authors.affiliation: Department of Information and Library Science, Indiana University, Bloomington, Indiana, United States of America; University Library, Tongji University, Shanghai, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Ding
authors.affiliation: Department of Information and Library Science, Indiana University, Bloomington, Indiana, United States of America.
authors.forename: Vincent
authors.initials: V
authors.lastname: Malic
mesh_terms: D001319:Authorship; D003299:Cooperative Behavior; D006801:Humans; D058025:Interdisciplinary Studies / Q000592:standards* / Q000639:trends; D011643:Publishing / Q000941:ethics* / Q000592:standards / Q000639:trends; D012108:Research Personnel / Q000941:ethics* / Q000592:standards / Q000639:trends