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 An Anomaly Detection Framework for Twitter Data Subject The topic of the resource anomaly detection; outlier detection; sentiment analysis; social media analytics; topic modeling Description An account of the resource An anomaly indicates something unusual, related to detecting a sudden behavior change, and is also helpful in detecting irregular and malicious behavior. Anomaly detection identifies unusual events, suspicious objects, or observations that differ significantly from normal behavior or patterns. Discrepancies in data can be observed in different ways, such as outliers, standard deviation, and noise. Anomaly detection helps us understand the emergence of specific diseases based on health-related tweets. This paper aims to analyze tweets to detect the unusual emergence of healthcare-related tweets, especially pre-COVID-19 and during COVID-19. After pre-processing, this work collected more than 44 thousand tweets and performed topic modeling. Non-negative matrix factorization (NMF) and latent Dirichlet allocation (LDA) were deployed for topic modeling, and a query set was designed based on resultant topics. This query set was used for anomaly detection using a sentence transformer. K-means was also employed for clustering outlier tweets from the cleaned tweets based on similarity. Finally, an unusual cluster was selected to identify pandemic-like healthcare emergencies. Experimental results show that the proposed framework can detect a sudden rise of unusual tweets unrelated to regular tweets. The new framework was employed in two case studies for anomaly detection and performed with 78.57% and 70.19% accuracy. 2022 by the authors. Creator An entity primarily responsible for making the resource Kumar S.; Khan M.B.; Hasanat M.H.A.; Saudagar A.K.J.; AlTameem A.; AlKhathami M. Source A related resource from which the described resource is derived Applied Sciences (Switzerland), Vol-12, No. 21 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/app122111059" target="_blank" rel="noreferrer noopener">https://doi.org/10.3390/app122111059</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141860286&amp;doi=10.3390%2Fapp122111059&amp;partnerID=40&amp;md5=4c87807537ebd56110bb7cf8419644f1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85141860286&amp;doi=10.3390%2fapp122111059&amp;partnerID=40&amp;md5=4c87807537ebd56110bb7cf8419644f1</a> Rights Information about rights held in and over the resource All Open Access; Gold Open Access Relation A related resource ISSN: 20763417 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 Kumar S., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Khan M.B., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Hasanat M.H.A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; Saudagar A.K.J., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; AlTameem A., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia; AlKhathami M., Information Systems Department, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia