INTEGRATION OF TEXT MINING AND COMPLEX SOCIAL NETWORK ANALYSIS For Quantitative Characterization of Discursive Evolution in Artificial Intelligence Through Streaming Platforms

Torres-Cruz F.; Yucra-Mamani Y.J.; Ibanez-Quispe V.; Mayta-Quispe M.F. · VISUAL Review. International Visual Culture Review / Revista Internacional de Cultura (2024) · DOI: 10.62161/revvisual.v16.5288

Resumen

This study provides a quantitative characterisation of the discursive evolution of Artificial Intelligence (AI) on streaming platforms (YouTube), integrating text mining and complex social network analysis. A comprehensive corpus was obtained from leading platforms, and natural language processing algorithms were implemented to analyse the textual content and identify patterns, emerging themes, and changes in AI discourses. Concurrently, a social network analysis was conducted to examine the interaction structures and the influence of different actors in the dissemination of information. The findings reveal significant trends in the representation and perception of AI, indicating the evolution of specific topics, differences in perception between different groups, and the influence of factors such as technological advances and global events. This analysis offers a more profound comprehension of the communication and perception of AI in the digital domain, providing valuable insights for academics, communicators and policymakers engaged in the field of AI.

Instituciones: Universidad Nacional del Altiplano