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@article{174182,
        author = {Narsingh Pal Yadav and Bhramari Anand and Dr. Bal Krishna Saraswat},
        title = {Prediction of indian election using Sentiment Analysis of Twitter},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {4627-4632},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174182},
        abstract = {social media is a collection of many online platforms that enables people to share contents with others. Social media has become big and massive platform to gather public opinions and sentiments in about any topics. Our study shows the potential of social media in the prediction of election outcomes. By analyzing public opinion, we will be able to identify voter behavior. Using machine learning techniques, we categorize social media post’s comment section to identify sentiment keys such as- positive, negative and neutral. By using ML algorithms, we will be able to evaluates the accuracy of sentiment analysis in election results. It will provide insights in to public moods and its growing importance in today’s time. This is evaluated using Naïve Bayes, SVM, and LSTM.},
        keywords = {Sentiment Analysis; Twitter; Indian Elections; Naive Bayes; Support Vector Machine; Long Short-Term Memory.},
        month = {April},
        }