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Smart City Data Sensing during COVID-19: Public Reaction to Accelerating Digital Transformation.

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Metropolis IT technologies adapted rapidly to address operational challenges during the COVID-19 pandemic. Analysis of Russian digital communications revealed transformations in existing and new digital services.

Keywords:
neural network technologiessmart citysocial mediaspeech perception

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Area of Science:

  • Information Science
  • Sociology
  • Computer Science

Background:

  • The COVID-19 pandemic necessitated rapid adaptation of information technology (IT) services in urban environments.
  • Operational challenges during the pandemic highlighted the need to analyze digital communication strategies.

Purpose of the Study:

  • To analyze the adaptation of metropolis IT technologies for operational problem-solving during the COVID-19 pandemic.
  • To examine the transformation and emergence of digital services based on public perception.

Main Methods:

  • Utilized a multimodal approach combining neural networks, text analysis, sentiment analysis, and lexical association analysis.
  • Analyzed a large dataset (85,493,717 characters) of Russian-language digital communications from March 1 to June 1, 2020.
  • Included data from social networks, blogs, forums, media, and other online platforms.

Main Results:

  • Identified significant adaptations in IT technologies to meet pandemic-related operational demands.
  • Observed transformations in existing digital services and the emergence of new ones.
  • Gained insights into public perception of digital communications during the crisis.

Conclusions:

  • Metropolis IT infrastructure demonstrated resilience and adaptability during the extreme conditions of the COVID-19 pandemic.
  • The study provides valuable insights into the evolution of digital services and user perception in crisis situations.