THIS ARTICLE PRESENTS a large-scale automated analysis of gender trends in the authorship of Computer Science literature. Specifcally, we aim to address the following questions: How is gender balance among authors changing over time. When might gender parity be reached among authors. How is gender associated with co-authorship. And how does Computer Science compare against other felds of study? We answer these questions by performing an automated study of literature metadata from scientifc conferences and journals, using data from the Semantic Scholar academic search engine.a Our study incorporates metadata from 11.8M Computer Science publications. To provide a basis for comparison, we also analyze more than 140M articles from other felds of study. Our results demonstrate that although progress has been made, there is still a signifcant gap in gender representation among Computer Science authors. Continued delay in addressing the gender gap may perpetuate imbalances for generations to come.
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