Multimodal fake news detection using text and image

dc.contributor.advisorSadeque,Farig Yousuf
dc.contributor.authorBiswas, Trisha
dc.contributor.authorLamia, Tasmim Afroj
dc.contributor.authorShykat, Tarikul Islam
dc.contributor.authorRafi, Md. Arifin Ahmed
dc.date.accessioned2024-04-23T05:29:03Z
dc.date.available2024-04-23T05:29:03Z
dc.date.issued2023-05
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 58-59).
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
dc.description.abstractDevelopment in information and technology has made the communication easier in the recent decades. Easy access of social media is creating restraints amid of differentiating fake and real news. In the recent period the problem has increased drastically and use of image is making the news more impactful. Even though news websites are publishing the news and provide the source of authentication still there are other portals and platform which intentionally spread fake news to exploit an event. In this paper we proposed a hybrid system where we are combining CNN and RNN to detect fake news . We applied two techniques to reduce the model complexity and increase accuracy based on text data and image. With this system, detecting fake news it’ll stop misleading people and creating an unstable situation as well as taking benefits of the situation.
dc.identifier.otherID: 20101628
dc.identifier.otherID: 19301190
dc.identifier.otherID: 19301008
dc.identifier.otherID: 19301009
dc.identifier.otherhttps://dspace.bracu.ac.bd/server/api/core/items/0854e900-e1a1-47aa-b014-85977f97e416
dc.identifier.urihttp://hdl.handle.net/10361/22652
dc.language.isoen
dc.publisherBRAC University
dc.sourceBRAC University Institutional Repository
dc.subjectNatural language processing
dc.subjectMultinomial naive bayes
dc.subjectBERT
dc.subjectBi-GRU
dc.subjectBi-LSTM
dc.subjectWord embedding
dc.subjectFake news
dc.subjectSupport vector machine
dc.titleMultimodal fake news detection using text and image
dc.typeThesis

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