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 Sentiment Analysis on Educational Tweets: A Case of National Education Policy 2020 Subject The topic of the resource machine learning; performance metrics; Sentiment analysis; sentiment score Description An account of the resource Due to COVID-19 pandemic lockdowns, the transition from traditional class-room-based approaches, there has been rise in online education. There is a growing need to adopt the best global academic and innovative practices and implement the National Education Policy-2020 (NEP) in Indian education. This study uses a dataset, NEPEduset, created by gathering tweets about education. An attempt has been made in this study to examine the tweets by preprocessing, generating labels or sentiments using standard tools and libraries in Python language, applying and comparing various machine learning (ML) algorithms. ML approaches are powerful and used in various applications ranging from sentiment analysis, text analysis, natural language processing (NLP), image processing, object detection. ML methods are widely used in sentiment analysis tasks and text annotations. This work uses Text-Blob, Valence Aware Dictionary for Sentiment Reasoning (VADER), and a Customized method, SentiNEP to analyze the sentiment score of tweets' text. SentiNEP method is shown is produce better results for various experiments conducted for the dataset, NEPEduset. Various supervised ML models have been applied for text classification of user sentiment. Word2Vec feature extraction technique has been applied to build and evaluate the models. Performance metrics such as precision, accuracy, F1 score and recall have been used to evaluate the ML models. The results reveal that the support vector machine and random forest classifiers achieve higher accuracy with Word2Vec. The performance results have been compared with VADER, TextBlob and SentiNEP. It has been found that the SentiNEP method produces better results. 2023 IEEE. Creator An entity primarily responsible for making the resource Siddique M.M.; Kumar S. Source A related resource from which the described resource is derived Proceedings of IEEE InC4 2023 - 2023 IEEE International Conference on Contemporary Computing and Communications 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/InC457730.2023.10262944" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/InC457730.2023.10262944</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174741364&amp;doi=10.1109%2FInC457730.2023.10262944&amp;partnerID=40&amp;md5=408f17b347bd680b0281c48ad8fc512d" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85174741364&amp;doi=10.1109%2fInC457730.2023.10262944&amp;partnerID=40&amp;md5=408f17b347bd680b0281c48ad8fc512d</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835033577-4 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 Siddique M.M., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Kengeri, Bengaluru, India; Kumar S., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Kengeri, Bengaluru, India