Yarovikov Andrey Sergeevich (Saint Petersburg State Institute of Technology (Technical University))
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The article discusses the possibilities of using data analysis methods in the information environment of a modern metropolis. The relevance of the topic is due to the increasing complexity of information flows, which require effective approaches to their processing and interpretation. The purpose of the study is to develop a comprehensive methodology for data analysis that takes into account the specifics of the megalopolis information environment. The tasks include a conceptual analysis of existing approaches, the development of terminology, and empirical testing of methods on a relevant sample. The methodology is based on a combination of statistical, semantic and network methods of data analysis. The empirical base consists of arrays of data from social media, urban information systems and sensor networks (with a total volume of over 10 GB). The following main results were obtained: 1) a classification of information flows of a megalopolis has been developed; 2) key patterns of information behavior of citizens have been identified; 3) factors of influence of the information environment on urban processes have been identified. The results have theoretical value for the development of Urban Data Science, as well as applied value for optimizing information policy and urban management.
Keywords:information environment of a megalopolis; urban data; data analysis methods; text mining; network analysis; machine learning
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Citation link:
Yarovikov A. S. APPLICATION OF DATA ANALYSIS METHODS IN THE INFORMATION ENVIRONMENT OF A MEGALOPOLIS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№04. -С. 174-177 DOI 10.37882/2223-2966.2025.04.50 |
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