Women and key positions in scientific collaboration networks

Analyzing central scientists’ profiles in the artificial intelligence ecosystem through a gender lens

Dados Bibliográficos

ID21443528
AutoresAnahita Hajibabaei (Concordia University), Andrea Schiffauerova (0000-0003-3349-3991, Concordia University), Ashkan Ebadi (0000-0002-4542-9105, National Academies of Sciences, Engineering, and Medicine, autor correspondente)
Ano2023
Volume128
Fascículo2
Páginas1219-1240
Data de publicação2023-02-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoScientometrics (JOURNAL)
Identificadores do periódicoISSN: 0138-9130 • E-ISSN: 1588-2861
EditoraSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11192-022-04601-5
OpenAlexW4311696862
IdiomaEN
Citações recebidas3
Referências citadas54

Scientific collaboration in almost every discipline is mainly driven by the need of sharing knowledge, expertise, and pooled resources. Science is becoming more complex which has encouraged scientists to involve more in collaborative research projects in order to better address the challenges. As a highly interdisciplinary field with a rapidly evolving scientific landscape, artificial intelligence calls for researchers with special profiles covering a diverse set of skills and expertise. Understanding gender aspects of scientific collaboration is of paramount importance, especially in a field such as artificial intelligence that has been attracting large investments. Using social network analysis, natural language processing, and machine learning and focusing on artificial intelligence publications for the period from 2000 to 2019, in this work, we comprehensively investigated the effects of several driving factors on acquiring key positions in scientific collaboration networks through a gender lens. It was found that, regardless of gender, scientific performance in terms of quantity and impact plays a crucial part in possessing the “social researcher” role in the network. However, subtle differences were observed between female and male researchers in acquiring the “local influencer” role

Data science · Field (mathematics) · Key (lock) · Knowledge management · Set (abstract data type) · Social media · Social network analysis · Sociology · World Wide Web · Artificial Intelligence · Computer Science · scientometrics and bibliometrics research