Deep learning diffusion by search trend: a country-level analysis

• Autor(a) principal: Takahashi, Carlos Kazunari
• Data de Publicação: 2023
• Outros Autores: Figueiredo, Júlio César Bastos de, Favaretto , José Eduardo Ricciardi
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Future Studies Research Journal: Trends and Strategies
• Texto Completo: https://www.revistafuture.org/FSRJ/article/view/695
• topic: Deep learning; Innovation diffusion; Search trend; Country-level analysis; BRICS; Google trends; Deep learning; Difusão de inovação; Search trend; Análise em nível de paí; BRICS; Google trends

Purpose: The theory of diffusion of innovation is the theoretical lens discussed in this research to analyze the diffusion of the deep learning theme in the BRICS and OECD countries. As little has been developed to understand country-level analysis and a theme such as innovation, this research sought to fill this gap. Originality/Value: This research demonstrates how it is possible to use Search Trends to analyze the diffusion of a thematic, enabling the extension of the diffusion of innovation theory beyond the sale of products. Methods: Google Trends was used for data collection and to provide up-to-date information, and two different statistical models were used: clustering to identify patterns in the first analysis, and the Bass diffusion model, aiming at comparing countries considering the curve peak, the innovation coefficient, and the imitation coefficient. Results: The findings of this research identified that China has the highest innovation coefficient among the members of the BRICS and Japan among the members of the OECD. Conclusions: This study brought both a theoretical contribution, allowing the expansion of the diffusion of innovations that use a theme as an object of innovation, as well as a practical implication, enabling research in an accessible and democratic way.