School of Systems Science, Beijing Normal University, Beijing 100875, China.
Department of Physics, Bar-Ilan University, Ramat-Gan 52900, Israel.
Proc Natl Acad Sci U S A. 2022 Aug 16;119(33):e2207436119. doi: 10.1073/pnas.2207436119. Epub 2022 Aug 8.
In scientific research, collaboration is one of the most effective ways to take advantage of new ideas, skills, and resources and for performing interdisciplinary research. Although collaboration networks have been intensively studied, the question of how individual scientists choose collaborators to study a new research topic remains almost unexplored. Here, we investigate the statistics and mechanisms of collaborations of individual scientists along their careers, revealing that, in general, collaborators are involved in significantly fewer topics than expected from a controlled surrogate. In particular, we find that highly productive scientists tend to have a higher fraction of single-topic collaborators, while highly cited-i.e., impactful-scientists have a higher fraction of multitopic collaborators. We also suggest a plausible mechanism for this distinction. Moreover, we investigate the cases where scientists involve existing collaborators in a new topic. We find that, compared to productive scientists, impactful scientists show strong preference of collaboration with high-impact scientists on a new topic. Finally, we validate our findings by investigating active scientists in different years and across different disciplines.
在科学研究中,合作是利用新思想、技能和资源以及进行跨学科研究的最有效方法之一。尽管合作网络已经得到了深入研究,但个体科学家如何选择合作者来研究一个新的研究课题这一问题几乎没有得到探索。在这里,我们研究了个体科学家在其职业生涯中的合作的统计数据和机制,揭示了合作者参与的主题通常比控制替代物所预期的要少。特别是,我们发现高产的科学家往往有更高比例的单主题合作者,而高引用的、即有影响力的科学家则有更高比例的多主题合作者。我们还提出了一个合理的机制来解释这种区别。此外,我们还研究了科学家在新课题中涉及现有合作者的情况。我们发现,与高产的科学家相比,有影响力的科学家在新课题上与高影响力的科学家合作的偏好更强。最后,我们通过研究不同年份和不同学科的活跃科学家来验证我们的发现。