While several previous studies have analyzed gender bias in research, we are
still missing a comprehensive analysis of gender differences in the AI
community, covering diverse topics and different development trends. Using the
AI Scholar dataset of 78K researchers in the field of AI, we identify several
gender differences: (1) Although female researchers tend to have fewer overall
citations than males, this citation difference does not hold for all
academic-age groups; (2) There exist large gender homophily in co-authorship on
AI papers; (3) Female first-authored papers show distinct linguistic styles,
such as longer text, more positive emotion words, and more catchy titles than
male first-authored papers. Our analysis provides a window into the current
demographic trends in our AI community, and encourages more gender equality and
diversity in the future. Our code and data are at
this https URL

本研究通过对 AI Scholar 数据集的分析，发现 AI 领域存在性别差异，包括论文引用、合著者中性别同质性和女性第一作者论文具有更长的文本长度、更多积极情感词和更容易引起读者注意的标题。这些发现有助于促进 AI 领域的性别平等和多样性。

分析 AI 出版世界中性别差异

Voices of Her: Analyzing Gender Differences in the AI Publication World

Using data from co-authorships at the international level in all fields of
science in 1990 and 2000, and within six case studies at the sub-field level in
2000, different explanations for the growth of international collaboration in
science and technology are explored. We find that few of the explanations
within the literature can be supported by a detailed review of the data. To
enable further exploration of the role of recognition and rewards as ordering
mechanisms within the system, we apply new tools emerging from network science.
These enquiries shows that the growth of international co-authorships can be
attributed to self-organizing phenomenon based on preferential attachment
(searching for recognition and reward) within networks of co-authors. The
co-authorship links can be considered as a complex network with sub-dynamics
involving features of both competition and cooperation. The analysis suggests
that the growth of international collaboration is more likely to emerge from
dynamics at the sub-field level operating in all fields of science, albeit
under institutional constraints. Implications for the management of global
scientific collaborations are explored.

探讨了科学技术国际合作的不同解释，并发现很少有文献可以得到数据的详细支持。通过应用网络科学的新工具，发现国际合著的增长可以归因于自组织现象。作者的共同作用联系可以被认为是一个涉及竞争和合作特点的复杂网络，为管理全球科学合作提供了启示。