Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Conference Papers Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Performance Analysis of Various Machine Learning Classification Models Using Twitter Data: National Education Policy Subject The topic of the resource classifier; Decision Tree; Gaussian Naive Bayes; Logistic Regression; Machine Learning; Natural Language Processing; Random Forest; Sentiment Analysis; Support Vector Machines; Twitter; XGBoost Description An account of the resource With the exponential growth of social networking sites, people are using these platforms to express their sentiments on everyday issues. Collection and analysis of people's reactions to purchases of products, public services, etc. are important from a marketing and innovation perspective. Sentiment analysis also called opinion mining or emotion extraction is the classification of emotions in text. This technique has been widely used over the years to determine sentiment within given text data. Twitter is a social media platform primarily used by people to express their feelings about specific events. In this paper, collected tweets about National Education Policy which has been a hot topic for a while; and analyzed them using various machine learning algorithms such as Random Forest classifier, Logistic Regression, SVM, Decision Tree, XGBoost, Naive Bayes. This study shows that the Decision tree algorithm is performing best, compare to all the other algorithms. 2023 IEEE. Creator An entity primarily responsible for making the resource Agarwal K.; Deepa S.; Sivabalan R.V.; Balakrishnan C. Source A related resource from which the described resource is derived Proceedings of the International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, ICIITCEE 2023, pp. 862-870. Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/IITCEE57236.2023.10091034" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/IITCEE57236.2023.10091034</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156107398&amp;doi=10.1109%2FIITCEE57236.2023.10091034&amp;partnerID=40&amp;md5=09b0f0af2fba2e04a41ce3d03fc7143f" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85156107398&amp;doi=10.1109%2fIITCEE57236.2023.10091034&amp;partnerID=40&amp;md5=09b0f0af2fba2e04a41ce3d03fc7143f</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166546263-1 Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Conference paper Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Agarwal K., Christ University, Department Computer Science, Bangalore, India; Deepa S., Christ University, Department Computer Science, Bangalore, India; Sivabalan R.V., Christ University, Department Computer Science, Bangalore, India; Balakrishnan C., Christ University, Department Computer Science, Bangalore, India