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Sentiment and Conflict Prediction in Urban Development: Data-Driven Approach

Author

Listed:
  • Nailia Gabdrakhmanova

    (Peoples Friendship University of Russia)

  • Maria Pilgun

    (Lomonosov Moscow State University
    Russian State Social University)

Abstract

The article presents a methodology for detecting and analyzing social tension in a metropolis using neural network and mathematical models built on time series. It considers the problem of assessing and predicting the development of the situation in real time, based on the content generated by users and their digital footprints, as illustrated by the implementation of a transport project. The integration of neural network and mathematical models made it possible to identify semantic negative accents, determine the features of project positioning in the media space, identify segments of the greatest informational attention, the level of social tension around the construction project, and also predict the development of the situation.

Suggested Citation

  • Nailia Gabdrakhmanova & Maria Pilgun, 2025. "Sentiment and Conflict Prediction in Urban Development: Data-Driven Approach," Springer Optimization and Its Applications,, Springer.
    • Handle: RePEc:spr:spochp:978-3-031-91357-0_5
    DOI: 10.1007/978-3-031-91357-0_5
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