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 A Comparative Study of ML and DL Approaches for Twitter Sentiment Classification Subject The topic of the resource comparative analysis; deep learning models; machine learning models; sentiment classification; text preprocessing; word embedding Description An account of the resource This research made use of various machine learning (ML) and deep learning (DL) methods - such as support vector machines, random forests, logistic regression, naive Bayes, and XGBoost, convolutional neural networks (CNNs), and feedforward neural networks (FNNs) - for tweet analysis to investigate public sentiment towards Ola and Uber. The objective is to determine the most effective method for distinguishing between good and negative tweets. Feature engineering techniques improve the algorithms interpretation of tweet content. To balance out the disparity between positive and negative tweets. The project aims to uncover customer wants and concerns on Twitter to help Ola and Uber, in addition to improving Algorithms Accuracy. The study intends to help these ride-hailing businesses make educated modifications to boost customer happiness by closely examining tweets. Essentially, the study assesses how well various ML and DL algorithms comprehend user feedback on Uber and Ola. The overarching goal is to not only enhance computational methods but also contribute to the improvement of these ride-hailing services, ultimately fostering a more positive online environment for Ola and Uber enthusiasts. In summary, the study investigates sentiment analysis techniques on Twitter to optimize understanding of Ola and Uber-related tweets, aiming to facilitate positive changes for the ride-hailing services and their customers, promoting a friendlier Twitter community. 2024 IEEE. Creator An entity primarily responsible for making the resource Aamir M.; Lekha J.; Sweety Source A related resource from which the described resource is derived 2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICEECT61758.2024.10738938" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICEECT61758.2024.10738938</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211083798&amp;doi=10.1109%2FICEECT61758.2024.10738938&amp;partnerID=40&amp;md5=5f17b046bbe2e93b3fc05222565a9218" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85211083798&amp;doi=10.1109%2fICEECT61758.2024.10738938&amp;partnerID=40&amp;md5=5f17b046bbe2e93b3fc05222565a9218</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 979-835037809-2 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 Aamir M., Christ (Deemed to be University), School of Science, Lavasa, India; Lekha J., Christ (Deemed to be University), School of Science, Lavasa, India; Sweety, Christ (Deemed to be University), School of Science, Lavasa, India