Dataset Information

Identifying author heritage using surname data: An application for Russian surnames.

ABSTRACT: This research article puts forward a method to identify the national heritage of authors based on the morphology of their surnames. Most studies in the field use variants of dictionary-based surname methods to identify ethnic communities, an approach that suffers from methodological limitations. Using the public file of ORCID (Open Researcher and Contributor ID) identifiers in 2015, we developed a surname-based identification method and applied it to infer Russian heritage from suffix-based morphological regularities. The method was developed conceptually and tested in an undersampled control set. Identification based on surname morphology was then complemented by using first-name data to eliminate false-positive results. The method achieved 98% precision and 94% recall rates-superior to most other methods that use name data. The procedure can be adapted to identify the heritage of a variety of national groups with morphologically regular naming traditions. We elaborate on how the method can be employed to overcome long-standing limitations of using name data in bibliometric datasets. This identification method can contribute to advancing research in scientific mobility and migration, patenting by certain groups, publishing and collaboration, transnational and scientific diaspora links, and the effects of diversity on the innovative performance of organizations, regions, and countries.

SUBMITTER: Karaulova M

PROVIDER: S-EPMC6853192 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying author heritage using surname data: An application for Russian surnames.

Karaulova Maria M Gök Abdullah A Shapira Philip P

Journal of the Association for Information Science and Technology 20190125 5

This research article puts forward a method to identify the national heritage of authors based on the morphology of their surnames. Most studies in the field use variants of dictionary-based surname methods to identify ethnic communities, an approach that suffers from methodological limitations. Using the public file of ORCID (Open Researcher and Contributor ID) identifiers in 2015, we developed a surname-based identification method and applied it to infer Russian heritage from suffix-based morp ...[more]

PMID: 31763359

Similar Datasets

Project description:IntroductionIn academia, many institutions use journal article publication productivity for making decisions on tenure and promotion, funding grants, and rewarding stellar scholars. Although non-alphabetical sequencing of article coauthoring by the spelling of surnames signals the extent to which a scholar has contributed to a project, many disciplines in academia follow the norm of alphabetical ordering of coauthors in journal publications. By assessing business academic publications, this study investigates the hypothesis that author alphabetical ordering disincentivizes teamwork and reduces the overall quality of scholarship.MethodsTo address our objectives, we accessed data from 21,353 articles published over a 20-year period across the four main business subdisciplines. The articles selected are all those published by the four highest-ranked journals (in each year) and four lower-ranked journals (in each year) for accounting, business technology, marketing, and organizational behavior. Poisson regression and binary logistic regression were utilized for hypothesis testing.ResultsThis study finds that, although team size among business scholars is increasing over time, alphabetical ordering as a convention in journal article publishing disincentivizes author teamwork. This disincentive results in fewer authors per publication than for publications using contribution-based ordering of authors. Importantly, article authoring teamwork is related to article quality. Specifically, articles written by a single author typically are of lesser quality than articles published by coauthors, but the number of coauthors exhibits decreasing returns to scale-coauthoring teams of one to three are positively related to high-quality articles, but larger teams are not. Alphabetical ordering itself, however, is positively associated with quality even though it inhibits teamwork, but journal article coauthoring has a greater impact on article quality than does alphabetical ordering.ConclusionsThese findings have important implications for academia. Scholars respond to incentives, yet alphabetical ordering of journal article authors conflicts with what is beneficial for the progress of academic disciplines. Based on these findings, we recommend that, to drive the highest-quality research, teamwork should be incentivized-all fields should adopt a contribution-based journal article author-ordering convention and avoid author ordering based upon the spelling of surnames. Although this study was undertaken using articles from business journals, its findings should generalize across all academia.

Dataset Information

Identifying author heritage using surname data: An application for Russian surnames.

Publications

Identifying author heritage using surname data: An application for Russian surnames.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets