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Understanding Team Collaboration in Artificial Intelligence from the perspective of Geographic Distance
arXiv - CS - Digital Libraries Pub Date : 2020-12-25 , DOI: arxiv-2012.13560
Xuli Tang, Xin Li, Ying Ding, Feicheng Ma

This paper analyzes team collaboration in the field of Artificial Intelligence (AI) from the perspective of geographic distance. We obtained 1,584,175 AI related publications during 1950-2019 from the Microsoft Academic Graph. Three latitude-and-longitude-based indicators were employed to quantify the geographic distance of collaborations in AI over time at domestic and international levels. The results show team collaborations in AI has been more popular in the field over time with around 42,000 (38.4%) multiple-affiliation AI publications in 2019. The changes in geographic distances of team collaborations indicate the increase of breadth and density for both domestic and international collaborations in AI over time. In addition, the United States produced the largest number of single-country and internationally collaborated AI publications, and China has played an important role in international collaborations in AI after 2010.

中文翻译:

从地理距离的角度了解人工智能中的团队合作

本文从地理距离的角度分析了人工智能(AI)领域的团队合作。我们在1950-2019年期间从Microsoft Academic Graph获得了1,584,175处与AI相关的出版物。三个基于纬度和经度的指标被用来量化国内外在一段时间内AI合作的地理距离。结果表明,随着时间的流逝,人工智能领域的团队合作在该领域越来越受欢迎,2019年约有42,000个(38.4%)的多分支机构AI出版物。团队合作的地理距离变化表明,国内和国外的广度和密度都在增加随着时间的流逝,人工智能领域的国际合作。此外,美国出版的单国和国际合作AI出版物数量最多,
更新日期:2020-12-29
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