2022/02/15 by Gangmin Son, Son, Gangmin, Jinhyuk Yun +3
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · Psychology · #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #Digital Libraries (cs.DL) #FOS: Computer and information sciences #FOS: Physical sciences #Mental Health Research Topics #Physics and Society (physics.soc-ph) #cs.DL #physics.soc-ph
paper · pdf · doi:10.48550/arxiv.2202.07252
arxiv created 2022/02/15 · openalex publication_date 2022/02/15 · arxiv updated 2022/02/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Team chemistry is the holy grail of understanding collaborative human behavior, yet its quantitative understanding remains inconclusive. To reveal the presence and mechanisms of team chemistry in scientific collaboration, we reconstruct the publication histories of 560,689 individual scientists and 1,026,196 duos of scientists. We identify ability discrepancies between teams and their members, enabling us to evaluate team chemistry in a way that is robust against prior experience of collaboration and inherent randomness. Furthermore, our network analysis uncovers a nontrivial modular structure that allows us to predict team chemistry between scientists who have never collaborated before. Research interest is the highest correlated ingredient of team chemistry among six personal characteristics that have been commonly attributed as the keys to successful collaboration, yet the diversity of the characteristics cannot completely explain team chemistry. Our results may lead to unlocking the hidden potential of collaboration by the matching of well-paired scientists.