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 Twitter Hate Speech Detection using Stacked Weighted Ensemble (SWE) Model Subject The topic of the resource Anomaly Detection; Ensemble Classification; Hard Voting and Soft Voting; Hate Speech; Linear Regression Model; Nae Bayes; Random Forest; Social Networking Services; Tweet Classification; Tweet Filtering Description An account of the resource Online Social Media has expanded the freedom of expression in the internet, which has become a disturbing problem if it has an impact on the situation or the interest of a country. Hate speech refers to the use of hostile, abusive or offensive language, directed at a certain group of people who share common property, whether it is their gender, ethnicity or race (i.e. racism), faith and religion. Therefore, auto detection of hate speeches has an increased importance in Online Social Media for filtering any message that has hatred language before posting it to the network. In this paper, a Stacked Weighted Ensemble (SWE) model is proposed for the detection of hate speeches. The model ensembles five standalone classifiers: Linear Regression, Nae Bayes', Random Forest, Hard Voting and Soft Voting. The experimental results on a Twitter dataset has shown an accuracy of 95.54% in binary classification of tweets into hateful speech and an improved performance is noted compared to the standalone classifiers. 2020 IEEE. Creator An entity primarily responsible for making the resource Kokatnoor S.A.; Krishnan B. Source A related resource from which the described resource is derived Proceedings - 2020 5th International Conference on Research in Computational Intelligence and Communication Networks, ICRCICN 2020, pp. 87-92. 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 2020-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ICRCICN50933.2020.9296199" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ICRCICN50933.2020.9296199</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099174302&amp;doi=10.1109%2FICRCICN50933.2020.9296199&amp;partnerID=40&amp;md5=b15f7285ec5202571b2d033e37fd1ef1" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85099174302&amp;doi=10.1109%2fICRCICN50933.2020.9296199&amp;partnerID=40&amp;md5=b15f7285ec5202571b2d033e37fd1ef1</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-172818818-8 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 Kokatnoor S.A., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India; Krishnan B., CHRIST (Deemed to Be University), Department of Computer Science and Engineering, Bangalore, India