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 Sentimental Analysis on Online Education Using Machine Learning Models Subject The topic of the resource Emotion classification; Machine learning; Natural language processing (NLP); Online education; Sentimental analysis Description An account of the resource Sentimental analysis is a simple natural language processing technique for classifying and identifying the sentiments and views represented in a source text. Corona pandemic has shifted the focus of education from traditional classrooms to online classes. Students mental and psychological states alter as a result of this transition. Sentimental study of the opinions of online education students can aid in understanding the students learning conditions. During the corona pandemic, only, students enrolled in online classes were surveyed. Only, students who are in college for pre-graduation, graduation, or post-graduation were used in this study. To grasp the pupils feelings, machine learning models were developed. Using the dataset, we were able to identify and visualize the students feelings. Students favorable, negative, and neutral opinions can be successfully classified using machine learning algorithms. The Naive Bayes method is the most accurate method identified. Logistic regression, support vector machine, decision tree, and random forest these algorithms also gave comparatively good accuracy. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Mathew S.T.; Jacob L. Source A related resource from which the described resource is derived Lecture Notes in Networks and Systems, Vol-462, pp. 413-422. Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Date A point or period of time associated with an event in the lifecycle of the resource 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-19-2211-4_37" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-19-2211-4_37</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135006728&amp;doi=10.1007%2F978-981-19-2211-4_37&amp;partnerID=40&amp;md5=2f8696eb7937a2c2085fcbbc9a3aea22" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85135006728&amp;doi=10.1007%2f978-981-19-2211-4_37&amp;partnerID=40&amp;md5=2f8696eb7937a2c2085fcbbc9a3aea22</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370; ISBN: 978-981192210-7 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 Mathew S.T., Department of Data Science, Christ University, Bengaluru, India; Jacob L., Department of Data Science, Christ University, Bengaluru, India