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Abstract <p>This article presents the results of a study of urban development conflict based on the analysis and interpretation of large volumes of social media data for making informed decisions on interaction with urban communities (Urban communities). A multimodal approach was used to analyze content, and algorithms were developed to analyze and interpret large volumes of text data using the TextAnalyst 2.32 and GPT4o neural network tools. Data analysis allowed us to identify semantic accents that provoke negative reactions from actors, analyze explicit and implicit opinions and assessments of residents, predict the prospects for the development of a conflict situation, and develop recommendations for the formation of a social design for the development of an urban area. As a result of the study, recommendations were developed for coordinating the infrastructure project with city residents, participation of the territory’s residents, and increasing the level of urban vitality.</p>

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Large-Scale Social Media Text Analysis for Enhanced Decision Making

  • 期刊论文

  • 发表日期：

    2025年12月1日

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  • A. A. Kharlamov,
  • A. N. Raskhodchikov,
  • M. A. Pilgun

摘要

Abstract

This article presents the results of a study of urban development conflict based on the analysis and interpretation of large volumes of social media data for making informed decisions on interaction with urban communities (Urban communities). A multimodal approach was used to analyze content, and algorithms were developed to analyze and interpret large volumes of text data using the TextAnalyst 2.32 and GPT4o neural network tools. Data analysis allowed us to identify semantic accents that provoke negative reactions from actors, analyze explicit and implicit opinions and assessments of residents, predict the prospects for the development of a conflict situation, and develop recommendations for the formation of a social design for the development of an urban area. As a result of the study, recommendations were developed for coordinating the infrastructure project with city residents, participation of the territory’s residents, and increasing the level of urban vitality.