
arXiv: 2309.09449
This paper study author simultaneously engaged in multiple affiliations based on bibliometric data covered in the Web of Science for the 2017-2021 period. Based on the affiliation information in publication records, we propose a general classification for multiple affiliations within-country or cross-country for analyzing authors' behavior in multiple affiliations and preferences of host countries across research fields. We find a decrease in publications led by international multi-affiliated authorship after 2020, and China has shown a falling trend after 2018. More G7 countries are active in fields like Social Sciences, Clinical and Life Sciences. China, India, and Russia are active in physical sciences-related fields. Countries prefer to affiliate with G7 countries, especially in Clinical and Life Sciences. These findings may provide more insights into the understanding of the behavior and productivity of multi-affiliated researchers in the current academic landscape.
FOS: Computer and information sciences, Computer Science - Digital Libraries, Digital Libraries (cs.DL)
FOS: Computer and information sciences, Computer Science - Digital Libraries, Digital Libraries (cs.DL)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
