Science, Technology, Engineering and Mathematics (STEM) disciplines are notorious for gender imbalance favouring men. From these, Computer Science appears to among the worst. The imbalance comes despite the fact that, the proportion of women publishing impactful papers has increased over the last couple of decades. Here, we explore the potential gender differences in collaboration dynamics of leading academics in Computer Science and contrast it with other researchers in the same discipline. This work aims to demonstrate that productivity patterns differ between men and women; understanding such patterns is fundamental to improving the current situation by driving well-thought interventions. We start by looking at topological features of academics ego-networks and their variability over their career lifespan; we found that women have a higher rate of repeated collaborators, while men have slightly more new collaborators. Second, we show gender differences in the acquisition patterns and maintenance of collaborations over the researchers’ careers. Third, we look at alters’ gender composition and gender role in introducing new collaborations to researchers and found that women are more homophilic than men and that the gender of the person being introduced (alter) tends to match the gender of the ego (the researcher). Last, we show that women reach their highest productivity levels earlier in their careers than men, but the levels attained are not at the same magnitude as men. Our work highlights the importance of studying gender differences by productivity levels, the role of gender-mixed groups in academia and the relation to academic production within these groups. This work contributes to a better understanding of gender roles in Computer Science and points to ways that can help reduce possible gaps.

中文翻译：

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登峰造极：计算机科学领域高级学者的性别效应

科学、技术、工程和数学 (STEM) 学科因有利于男性的性别失衡而臭名昭著。从这些来看，计算机科学似乎是最差的。尽管在过去几十年中发表有影响力的论文的女性比例有所增加，但这种不平衡仍然存在。在这里，我们探讨了计算机科学领域领先学者的合作动态中潜在的性别差异，并将其与同一学科的其他研究人员进行了对比。这项工作旨在证明男性和女性之间的生产力模式不同；了解这种模式对于推动深思熟虑的干预措施来改善当前状况至关重要。我们首先研究学者自我网络的拓扑特征及其在职业生涯中的可变性；我们发现女性的重复合作者比例更高，而男性的新合作者略多。其次，我们展示了研究人员职业生涯中获取模式和合作维护的性别差异。第三，我们研究了改变者在向研究人员介绍新合作时的性别构成和性别角色，发现女性比男性更具有同性恋倾向，并且被介绍的人（alter）的性别往往与自我的性别相匹配（研究人员）。最后，我们展示了女性在职业生涯中比男性更早地达到最高生产力水平，但达到的水平与男性不同。我们的工作强调了按生产力水平研究性别差异的重要性，性别混合群体在学术界的作用以及与这些群体内的学术生产的关系。这项工作有助于更好地理解计算机科学中的性别角色，并指出可以帮助减少可能存在的差距的方法。