Development of Tools for Studying the Practices of Using AI by Residents of a Megalopolis: Methodology and Analysis
There are many aspects of social interaction associated with the use of artificial intelligence technologies in everyday life, which makes the study of such practices among residents of a megalopolis an important area of research. In a megalopolis, the use of AI covers a variety of areas, which requires an integrated approach to data collection and analysis. The article discusses a methodological approach to studying the practices of using artificial intelligence (AI) technologies among the residents of a megalopolis, based on automated analysis of open data. Based on the pilot study, key sources of information and their analytical potential for further in-depth study are evaluated. The authors present a combined method aimed at identifying the differentiation of practices in the application of AI. To study the practices of using AI, an approach was applied that includes automated data collection and analysis: open data research using parsing and machine learning methods, which allows us to identify trends and features of the use of AI. Main data sources for the analysis include: Telegram bots and channels dedicated to AI; Mobile app from the Store Market using AI technology, the company profiles on Google Maps and Yandex.Maps that demonstrate the use of AI, social networks, and media outlets that publish information about AI. As part of the pilot testing, data was collected from these sources. The results confirmed that each source provides valuable data for the analysis of AI-based tools and services. This confirms the expediency of using these sources to identify differences in AI usage practices. The pilot study showed that automated data analysis technologies can be effective for studying the practices of using AI in a megacity. In the future, it is planned to conduct a more in-depth data analysis to identify patterns and trends in the use of AI technologies among various social groups in the metropolis.
Authors
- Boris Nizomutdinov (ORCID: https://orcid.org/0000-0002-4090-9564)
Institutions
- ITMO University (RU)
Publication Details
- Published
- 2025-04-09
- DOI
- https://doi.org/10.1109/comsds65569.2025.10971292
- Primary Topic
- BIM and Construction Integration
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Russian Science Foundation