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 Fake News Detection and Classify the Category Subject The topic of the resource Artificial Intelligence; Logistic Regression; Machine Learning; Multi-layer Perceptron; Natural Language Processing; Random Forest; Support Vector Machine Description An account of the resource Everyone depends on numerous sources of E-news in today's world when the internet is ubiquitous. Online content abounds, especially social media feeds, many of which are unreliable and may not always be factual. For people to utilise social media platforms like Facebook, Twitter, and others, fake news is a topic that may be studied through Natural Language Processing techniques. Using ideas from natural language processing and machine learning applied to social media, our goal in this work is to conduct categorization of different news items that are available online. Our intention is to empower the user to utilise NLP (Natural Language Processing) methods to identify 'fake news,' which refers to misinformed material that may be categorised as genuine or false using software like Python. The model focuses on identifying false news sources based on several articles from a website, categorising the news as false or true, and determining its veracity using unreliable sources like scikit-learn and NLP for textual analysis of the website distributing the news. When a source is identified as a publisher of false news, which can be predicted with high vectorization and also suggested using the Python scikit-learn module to do tokenization and feature development, biased viewpoints may be identified and categorised in any subsequent articles from that source. 2022 IEEE. Creator An entity primarily responsible for making the resource Mitra P.; Jacob L. Source A related resource from which the described resource is derived 2022 International Conference on Trends in Quantum Computing and Emerging Business Technologies, TQCEBT 2022 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 2022-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/TQCEBT54229.2022.10041596" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/TQCEBT54229.2022.10041596</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149182145&amp;doi=10.1109%2FTQCEBT54229.2022.10041596&amp;partnerID=40&amp;md5=00e69431597f7985c16388c24548f01e" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149182145&amp;doi=10.1109%2fTQCEBT54229.2022.10041596&amp;partnerID=40&amp;md5=00e69431597f7985c16388c24548f01e</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISBN: 978-166545361-5 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 Mitra P., Christ University Pune, Lavasa Campus, Department of Data Science, Pune, India; Jacob L., Christ University Pune, Lavasa Campus, Department of Data Science, Pune, India