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@article{199106,
        author = {Niranjana R and Kalaiselvan B and Nandhaakash.M and Ranjithkumar.G},
        title = {NLP based Grievance Redressal System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {11},
        pages = {12636-12640},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=199106},
        abstract = {Internet is almost accessed by every individual and for expressing themselves and their thinking about the Politics, Country, Sports, and various other topics. Analyzing these trends of the public, can yield various result for variety of purposes. Social Media platforms are also used by several government ministries, mostly Twitter, as its main purpose is data sharing and complaint accumulation. By this, one can collect various data, sentiments, knowledge, and requirements of citizens by applying analyzing citizen sourcing ideas to provide better public service. It is hard to search for the complaint tweets, as these tweets have high velocity and are unstructured in nature. The study provides a framework that helps the Railway Ministry to classify the tweets into complaints/suggestions and compliments. The research shows the usage of Natural Language Processing (NLP) and sentiment analysis for the classification of tweets as the data set is written as general spoken language. The accuracy of the framework is 95.8%.},
        keywords = {Natural Language Processing, Sentiment Analysis, Twitter Analysis, Naïve Bayes, Decision Tree, Random Forest, Correlation and Regression},
        month = {April},
        }