论文标题
妇女，人工智能和协作网络中的关键立场：迈向更平等的科学生态系统
Women, artificial intelligence, and key positions in collaboration networks: Towards a more equal scientific ecosystem
论文作者
论文摘要
几乎每个学科的科学合作主要是由共享知识，专业知识和汇集资源的需要驱动的。科学变得越来越复杂，它鼓励科学家更多地参与协作研究项目，以更好地应对挑战。作为一个高度跨学科的领域，具有迅速发展的科学景观，人工智能呼吁为研究人员提供涵盖各种技能和专业知识的特殊概况的研究人员。了解科学合作的性别方面至关重要，尤其是在吸引大型投资的人工智能等领域。使用社交网络分析，自然语言处理以及机器学习，并专注于2000年至2019年的人工智能出版物，在这项工作中，我们全面研究了几个驱动因素对通过性别镜头在科学协作网络中获取关键位置的影响。据研究发现，无论性别如何，在数量和影响方面的科学表现对于在网络中拥有“社会研究人员”至关重要。但是，在获得“本地影响者”角色时，男女研究人员之间观察到细微的差异。
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 in possessing the "social researcher" in the network. However, subtle differences were observed between female and male researchers in acquiring the "local influencer" role.
