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 Book Chapter Book Chapter Faculty Publications- Book Chapter 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 Novel Auto Encoder- Network- Based Ensemble Technique for Sentiment Analysis Using Tweets on COVID- 19 Data Description An account of the resource The advances in digitalization have resulted in social media sites like Twitter and Facebook becoming very popular. People are able to express their opinions on any subject matter freely across the social media networking sites. Sentiment analysis, also termed emotion artificial intelligence or opinion mining, can be considered a technique for analyzing the mood of the general public on any subject matter. Twitter sentiment analysis can be carried out by considering tweets on any subject matter. The objective of this research is to implement a novel algorithm to classify the tweets as positive or negative, based on machine learning, deep learning, the nature inspired algorithm and artificial neural networks. The proposed novel algorithm is an ensemble of the decision tree algorithm, gradient boosting, Logistic Regression and a genetic algorithm based on the auto-encoder technique. The dataset under consideration is tweets on COVID-19 in May 2021. 2024 Taylor &amp; Francis Group, LLC. Creator An entity primarily responsible for making the resource Jyothsna R.; Rohini V.; Paulose J. Source A related resource from which the described resource is derived Machine Intelligence: Computer Vision and Natural Language Processing, pp. 257-272. Publisher An entity responsible for making the resource available CRC Press 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/10.1201/9781003424550-14" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003424550-14</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173359844&amp;doi=10.1201%2F9781003424550-14&amp;partnerID=40&amp;md5=55d5e5402de5728b2b231c0b7073ed7a" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173359844&amp;doi=10.1201%2f9781003424550-14&amp;partnerID=40&amp;md5=55d5e5402de5728b2b231c0b7073ed7a</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100096031-0; 978-103220199-3 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 Book chapter Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Jyothsna R., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Rohini V., Department of Computer Science, Christ University, Karnataka, Bangalore, India; Paulose J., Department of Computer Science, Christ University, Karnataka, Bangalore, India