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 comparative study of text mining algorithms for anomaly detection in online social networks Subject The topic of the resource Anomaly detection; Decision trees; Entropy and Euclidean distance; Gini index; K-Nearest neighbour (KNN) and Support Vector Machine (SVM); Kernel function; Rocchio algorithm; Social media Description An account of the resource Text mining is a process by which information and patterns are extracted from textual data. Online Social Networks, which have attracted immense attention in recent years, produces enormous text data related to the human behaviours based on their interactions with each other. This data is intrinsically unstructured and ambiguous in nature. The data involves incorrect spellings and inaccurate grammars leading to lexical, syntactic and semantic ambiguities. This causes wrong analysis and inappropriate pattern identification. Various Text Mining approaches are being used by researchers which can help in Anomaly Detection through Topic Modeling, identification of Trending Topics, Hate Speeches and evolution of the communities in Online Social Networks. In this paper, a comparative analysis of the performance of four classification algorithms, Support Vector Machine (SVM), Rocchio, Decision Trees and K-Nearest Neighbour (KNN) for a Twitter data set is presented. The experimental study revealed that SVM outperforms better than other classifiers, and also classifies the dataset into anomalous and non-anomalous users opinions. The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2021. 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 Lecture Notes in Networks and Systems, Vol-132, pp. 29-37. Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2021-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-981-15-5309-7_4" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-981-15-5309-7_4</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090369987&amp;doi=10.1007%2F978-981-15-5309-7_4&amp;partnerID=40&amp;md5=832032cda9a14a0f1b467866b8cb5734" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090369987&amp;doi=10.1007%2f978-981-15-5309-7_4&amp;partnerID=40&amp;md5=832032cda9a14a0f1b467866b8cb5734</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 23673370 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 Kokatnoor S.A., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Krishnan B., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India