Prioritizing Public Grievance Redressal Using Text Mining and Sentimental Analysis

  • Rama Krushna DasEmail author
  • Manisha Panda
  • Sweta Shree Dash
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1082)


After successful implementation of online grievance monitoring systems by different government agencies, the grievance submission by common citizen has increased many folds. As the number exponentially increases, it becomes difficult for the government authorities to redress the grievances timely, efficiently, and effectively. In this paper, the authors are proposing different text mining and sentimental analysis techniques, on the content of the grievance, to prioritize the grievances submitted to the Chief Minister (CM) grievance cell, Odisha Province. Using these techniques, the grievances are prioritized as high priority, medium priority, and low priority. It helps the concerned government authorities to redress the top priority grievances within a stipulated time period, in comparison to medium and low priority grievances. This helps the needy and common citizen to get timely public services and government support, and their faith and confidence increases on the government machinery.


Text mining Sentiment analysis Lexicon Afinn Bing Grievance Grievance redressal High priority Medium priority Low priority 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Rama Krushna Das
    • 1
    Email author
  • Manisha Panda
    • 2
  • Sweta Shree Dash
    • 3
  1. 1.National Informatics CentreBerhampurIndia
  2. 2.Berhampur UniversityBerhampurIndia
  3. 3.Institute of Technical Education and ResearchBhubaneswarIndia

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