[Purpose/Significance] This study examines the development status of open-source AI code and explores strategies for identifying its high-value from a developer’s perspective. These findings provide valuable insights and references for information resource managers and users in the management and utilization of opensource AI code. [Method/Process] Using open-source AI code on GitHub as a case, this study investigates overall development trends and the distribution of developer characteristics, and further examines cross-country differences from three core dimensions: contribution, leadership, and influence. Furthermore, this study explores the predictive role of different development approaches and developer characteristics in these three key dimensions. [Result/Conclusion] Open-source AI code exhibits a continuous growth trend, with the United States maintaining a dominant position in terms of contribution, leadership, and influence. The key predictive factors include development approaches, the composition of developer communities, participation activity levels, and national technological capabilities.
Jiang Jingyi
,
Li Guangjian
,
Pan Jiali
. Analysis of Open-Source Artificial Intelligence Code from a Developer’s Perspective[J]. Library and Information Service, 2026
, 70(2)
: 86
-98
.
DOI: 10.13266/j.issn.0252-3116.2026.02.007
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