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 Articles Article Faculty Publications -Articles 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 Semantic Analysis and Topic Modelling of Web-Scrapped COVID-19 Tweet Corpora through Data Mining Methodologies Subject The topic of the resource BiLSTM; COVID-19 sentiment analysis; Latent Dirichlet Allocation (LDA); natural language processing; topic modeling Description An account of the resource The evolution of the coronavirus (COVID-19) disease took a toll on the social, healthcare, economic, and psychological prosperity of human beings. In the past couple of months, many organizations, individuals, and governments have adopted Twitter to convey their sentiments on COVID-19, the lockdown, the pandemic, and hashtags. This paper aims to analyze the psychological reactions and discourse of Twitter users related to COVID-19. In this experiment, Latent Dirichlet Allocation (LDA) has been used for topic modeling. In addition, a Bidirectional Long Short-Term Memory (BiLSTM) model and various classification techniques such as random forest, support vector machine, logistic regression, naive Bayes, decision tree, logistic regression with stochastic gradient descent optimizer, and majority voting classifier have been adapted for analyzing the polarity of sentiment. The effectiveness of the aforesaid approaches along with LDA modeling has been tested, validated, and compared with several benchmark datasets and on a newly generated dataset for analysis. To achieve better results, a dual dataset approach has been incorporated to determine the frequency of positive and negative tweets and word clouds, which helps to identify the most effective model for analyzing the corpora. The experimental result shows that the BiLSTM approach outperforms the other approaches with an accuracy of 96.7%. 2022 by the authors. Licensee MDPI, Basel, Switzerland. Creator An entity primarily responsible for making the resource Gourisaria M.K.; Chandra S.; Das H.; Patra S.S.; Sahni M.; Leon-Castro E.; Singh V.; Kumar S. Source A related resource from which the described resource is derived Healthcare (Switzerland), Vol-10, No. 5 Publisher An entity responsible for making the resource available MDPI 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/10.3390/healthcare10050881" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/healthcare10050881</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130318553&amp;doi=10.3390%2Fhealthcare10050881&amp;partnerID=40&amp;md5=f406b997b389f51e257aecb8692b61b4" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85130318553&amp;doi=10.3390%2fhealthcare10050881&amp;partnerID=40&amp;md5=f406b997b389f51e257aecb8692b61b4</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access; Green Open Access Relation A related resource ISSN: 22279032 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 Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gourisaria M.K., School of Computer Engineering, KIIT Deemed to be University, Odisha, Bhubaneswar, 751024, India; Chandra S., School of Computer Engineering, KIIT Deemed to be University, Odisha, Bhubaneswar, 751024, India; Das H., School of Computer Engineering, KIIT Deemed to be University, Odisha, Bhubaneswar, 751024, India; Patra S.S., School of Computer Applications, KIIT Deemed to be University, Odisha, Bhubaneswar, 751024, India; Sahni M., Department of Mathematics, Pandit Deendayal Energy University, Gujarat, Gandhinagar, 382426, India; Leon-Castro E., Faculty of Economics and Administrative Sciences, Universidad Catica de la Santima Concepci, Concepci, 4030000, Chile; Singh V., Department of Computer Science and Engineering, School of Computing and Information Technology, Manipal University Jaipur, Rajasthan, Jaipur, 303007, India, ERCIM Postdoctoral Fellow, Department of ICT and Science, Norwegian University of Science and Technology, Ankeret, B-315, esund, Torgarden, Trondheim, 7491, Norway; Kumar S., Department of CSE, School of Engineering and Technology, CHRIST Deemed to be University, Karnataka, Bengaluru, 560029, India