International collaboration has become imperative in the field of AI. However, few studies exist concerning how distance factors have affected the international collaboration in AI research. In this study, we investigate this problem by using 1,294,644 AI related collaborative papers harvested from the Microsoft Academic Graph (MAG) dataset. A framework including 13 indicators to quantify the distance factors between countries from 5 perspectives (i.e., geographic distance, economic distance, cultural distance, academic distance, and industrial distance) is proposed. The relationships were conducted by the methods of descriptive analysis and regression analysis. The results show that international collaboration in the field of AI today is not prevalent (only 15.7%). All the separations in international collaborations have increased over years, except for the cultural distance in masculinity/felinity dimension and the industrial distance. The geographic distance, economic distance and academic distances have shown significantly negative relationships with the degree of international collaborations in the field of AI. The industrial distance has a significant positive relationship with the degree of international collaboration in the field of AI. Also, the results demonstrate that the participation of the United States and China have promoted the international collaboration in the field of AI. This study provides a comprehensive understanding of internationalizing AI research in geographic, economic, cultural, academic, and industrial aspects.
翻译:在这项研究中,我们通过使用从微软学术图(MAG)数据集中获取的1,294,644份AI相关合作文件来调查这一问题。一个框架包括13项指标,用以从5个角度(即地理距离、经济距离、文化距离、学术距离和工业距离)量化国家间的距离因素。提出了从5个角度(即地理距离、经济距离、文化距离、学术距离和工业距离)量化因素的框架。工业距离与AI领域国际合作的程度有着显著的积极关系。结果还表明,如今AI领域的国际合作并不普遍(只有15.7%)。国际合作中的所有分离现象多年来都有所增加,除了男性/女性方面的文化距离和工业距离之外。这一研究从地理距离、经济距离和学术距离与AI领域国际合作的程度显示出显著的负面关系。工业距离与AI领域的国际合作程度有着显著的积极关系。此外,结果显示,美国和中国参与AI领域国际合作的情况并不普遍(只有15.7%)。