Measuring biases in AI-generated co-authorship networks
Abstract Large Language Models (LLMs) have significantly advanced prompt-based information retrieval, yet their potential to reproduce or amplify social biases remains insufficiently understood. In this study, we investigate this issue through the concrete task of reconstructing real-world co-author...
Saved in:
| Main Authors: | Ghazal Kalhor, Shiza Ali, Afra Mashhadi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2025-05-01
|
| Series: | EPJ Data Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1140/epjds/s13688-025-00555-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Co-authorship Network and Citation Analysis of Health Knowledge Management Researchers
by: Sirous Panahi, et al.
Published: (2025-07-01) -
Three decades of collaboration in rheumatology: a comprehensive co-authorship network analysis (1994–2023)
by: Naruaki Ogasawara
Published: (2025-04-01) -
Social Network Analysis of the Co-authorship Network in the Scientific Articles of Information Systems
by: Amir Hossein Mardani, et al.
Published: (2015-12-01) -
Terminating and Leaving a Union in Co-Authorship
by: Furkan Derdiman
Published: (2023-03-01) -
Estudo da rede de co-autoria e da interdisciplinaridade na produção científica com base nos métodos de análise de redes sociais: avaliação do caso do programa de pós-graduação em ciência da informação - PPGCI / UFMG <p> Study of co-authorship in the nets and the interdisciplinarity in the scientific production on the basis of social network analysis methods: evaluation of the posgraduation program in information science - PPGCI / UFMG
by: Antonio Braz de Oliveira e Silva, et al.
Published: (2006-01-01)