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 Performance analysis of semantic veracity enhance (SVE) classifier for fake news detection and demystifying the online user behaviour in social media using sentiment analysis Subject The topic of the resource Fake news detection; Online user behaviour; Semantic veracity enhancement (SVE); Sentiment analysis; Twitter Description An account of the resource The increased propagation of fake news is the significant concern in the digital era. Identification of fake news from social media platforms is critical to strengthen public trust and ensure social stability. This research presents an effective and accurate framework for identifying fake news that combines different steps of natural language processing (NLP) technique along with a neural network architecture. A novel semantic veracity enhancement (SVE) classifier is designed and implemented in this work for detecting fake news. The proposed approach leverages the effectiveness of sentiment analysis for identifying misleading or deceptive content and its subsequent implications on the sentiment and behaviour of social media users. A BERT model is used in this research for analysing the sentiments and classifying the texts from the social media platform. By examining the sentiments, the SVE classifier differentiates between real news and fabricated content. To achieve this, three different datasets comprising both actual content and fabricated (tweaked) tweets are employed for training the SVE classifier. The potentiality of the SVE classifier is evaluated and compared with different optimization techniques. The outcome of the experimental analysis shows that the proposed approach exhibits an excellent performance in terms of classifying misinformation from the original information with an outstanding accuracy of 99% compared to other state of art methods. 2024, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature. Creator An entity primarily responsible for making the resource Sethurajan M.R.; Natarajan K. Source A related resource from which the described resource is derived Social Network Analysis and Mining, Vol-14, No. 1 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 2024-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s13278-024-01199-9" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s13278-024-01199-9</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183650929&amp;doi=10.1007%2Fs13278-024-01199-9&amp;partnerID=40&amp;md5=5e35976b71bdee3e38fa009d165f4131" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183650929&amp;doi=10.1007%2fs13278-024-01199-9&amp;partnerID=40&amp;md5=5e35976b71bdee3e38fa009d165f4131</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 18695450 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 Sethurajan M.R., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India; Natarajan K., Department of Computer Science and Engineering, School of Engineering and Technology, CHRIST (Deemed to be University), Kengeri Campus, Karnataka, Bengaluru, 560074, India