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 Detection of toxic comments over the internet using deep learning methods Subject The topic of the resource BER; BERT; BidirectionalLSTM; Finetuning; Hate speech; Language model; Neural networks; Pretraining; Sentiment analysis; Social media; Toxic; Toxic comment; Twitter Description An account of the resource People now share their ideas on a wide range of topics on social media, which has become an integral part of contemporary culture. The majority of people are increasingly turning to social media as a necessity, and there are numerous incidents of social media addiction that have been reported. Socialmedia channels. Socialmedia platforms have established their worth over time by bringing individuals from different backgrounds together, but they have also shown harmful side effects that could have serious consequences. One such unfavourable result is how extremely poisonous many discussions on social media are. Online abuse, hate speech, and occasionally outrage culture are now all considered to be toxic. In this study, we leverage the Transformers Bidirectional Encoder Representations to build an efficient model to detect and classify toxicity in user-generated content on social media. The Kaggle dataset with labelled toxic comments, was used to refine the BERT pre-trained model. Other Deep learning models, including Bidirectional LSTM, Bidirectional-LSTM with attention, and a few other models, were also tested to see which performed best in this classification task. We further evaluate the proposed models utilising dataset obtained from Twitter in order to find harmful content (tweets) using relevant hashtags. The findings showed how well the suggested methodology classified and analysed toxic comments. 2024 selection and editorial matter, Arvind Dagur, Karan Singh, Pawan Singh Mehra &amp; Dhirendra Kumar Shukla; individual chapters, the contributors. Creator An entity primarily responsible for making the resource Naskar A.; Harchandani R.; Thomas K.T. Source A related resource from which the described resource is derived Artificial Intelligence, Blockchain, Computing and Security: Volume 1, Vol-1, pp. 447-454. Publisher An entity responsible for making the resource available CRC Press Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1201/9781003393580-68" target="_blank" rel="noreferrer noopener">https://doi.org/10.1201/9781003393580-68</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180023049&amp;doi=10.1201%2F9781003393580-68&amp;partnerID=40&amp;md5=e6e8bf2b156b8eec2d4e59b40ecdf4c3" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180023049&amp;doi=10.1201%2f9781003393580-68&amp;partnerID=40&amp;md5=e6e8bf2b156b8eec2d4e59b40ecdf4c3</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-100384581-2; 978-103249393-0 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 Naskar A., Department of Data Science, Department of Data Science CHRIST (Deemed to be University) Pune, CHRIST (Deemed to be University), Maharashtra, Lavasa, Pune, Lavasa, India; Harchandani R., Department of Data Science, Department of Data Science CHRIST (Deemed to be University) Pune, CHRIST (Deemed to be University), Maharashtra, Lavasa, Pune, Lavasa, India; Thomas K.T., Department of Data Science, Department of Data Science CHRIST (Deemed to be University) Pune, CHRIST (Deemed to be University), Maharashtra, Lavasa, Pune, Lavasa, India