Women and key positions in scientific collaboration networks: analyzing central scientists' profiles in the artificial intelligence ecosystem through a gender lens

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.

Automated summary

Scientific collaboration is driven by the need for sharing knowledge and resources, and the increasing complexity of science has led to more collaborative research in order to address challenges. Understanding the gender aspects of collaboration, particularly in the field of artificial intelligence, is important due to its significant investments. This study used social network analysis, natural language processing, and machine learning to examine the effects of factors on acquiring key positions in collaboration networks, with a focus on artificial intelligence publications from 2000 to 2019. Results showed that scientific performance is crucial for the social researcher role regardless of gender, but subtle differences were observed between female and male researchers in acquiring the local influencer role.