Abstract
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.
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Das, R.K., Panda, M., Dash, S.S. (2020). Prioritizing Public Grievance Redressal Using Text Mining and Sentimental Analysis. In: Pati, B., Panigrahi, C., Buyya, R., Li, KC. (eds) Advanced Computing and Intelligent Engineering. Advances in Intelligent Systems and Computing, vol 1082. Springer, Singapore. https://doi.org/10.1007/978-981-15-1081-6_23
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DOI: https://doi.org/10.1007/978-981-15-1081-6_23
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