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Public opinion mining using natural language processing technique for improvisation towards smart city.

S Leelavathy1, M Nithya2

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Summary

This study introduces an e-governance platform using natural language processing to manage public grievances and COVID-19 alerts. It efficiently routes voice inputs to relevant departments and emergency services, enhancing citizen engagement.

Keywords:
Covid 19Fuzzy logicHidden Markov modelsNatural language processingSpeech processing

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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Public Administration

Background:

  • Smart city concepts necessitate robust e-governance applications for public feedback and grievance redressal.
  • Existing platforms lack mechanisms for collecting and acting on public opinions regarding health crises like COVID-19 or government policies.
  • The proliferation of opinion-rich data presents opportunities for developing intelligent systems to process public messages.

Purpose of the Study:

  • To develop an efficient e-governance platform leveraging natural language processing for public voice input analysis.
  • To enable automatic detection of COVID-19 related concerns and alert relevant authorities and emergency services.
  • To create a transparent system for monitoring public grievances and government responses.

Main Methods:

  • Voice messages converted to text using Hidden Markov Models (HMMs).
  • Natural Language Processing techniques including pre-processing, part-of-speech tagging, and n-gram analysis were employed.
  • Fuzzy logic, a machine learning technique, was utilized for identifying the responsible government department.
  • Automated alerts via email/message to officials and nearby ambulances for COVID-19 cases, alongside a ticketing system for monitoring.

Main Results:

  • The integration of HMMs and Fuzzy Logic demonstrated promising results in processing public voice inputs.
  • The developed Java-based web and mobile application successfully executed the proposed methodology.
  • The system effectively identified responsible departments and initiated timely alerts for COVID-19 related issues.

Conclusions:

  • The proposed e-governance platform offers an effective solution for managing public grievances and health alerts.
  • Natural language processing and machine learning techniques can significantly enhance the efficiency of e-governance systems.
  • The system promotes transparency and responsiveness in government services, particularly during public health emergencies.