Open-Source AI Community as “Trading Zone”: The Role of Open-Source Models in the Diffusion of Artificial Intelligence Innovation

Previous studies have highlighted the role of computational models in the diffusion of AI research, suggesting that the impact of models extends beyond their mere existence. In our analysis, which encompasses 64,059 papers and 98,105 models from 2000 to 2023, we adopt a twofold approach, integrating Graph Neural Network (GNN) and traditional network analysis to provide complementary insights. We discovered that a model’s dependency network significantly influences paper citations and warrants further attention. Notably, the placement of focal versus offspring models in relation to a paper markedly affects its diffusion. Our findings enrich the literature on AI innovation diffusion by underscoring the critical importance of models and their networks. Additionally, our work enhances the GNN literature by advancing the capabilities of existing explainers to accommodate the nuances of temporal network structures