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dc.contributor.advisorIslam, MD Saiful
dc.contributor.advisorRahman, Rafeed
dc.contributor.authorIslam, Kazi Minhazul
dc.contributor.authorReza, Md. Safkat
dc.contributor.authorYeaser, MD. Samin
dc.date.accessioned2022-01-04T06:14:54Z
dc.date.available2022-01-04T06:14:54Z
dc.date.copyright2021
dc.date.issued2021-09
dc.identifier.otherID 17101456
dc.identifier.otherID 17101106
dc.identifier.otherID 17301063
dc.identifier.urihttp://hdl.handle.net/10361/15823
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 19-21).
dc.description.abstractIt is an age of the Web and electronic media, and social media stages are one of the foremost frequently used communication mediums these days. But a few individuals utilize these platforms for a noxious reason and among those negative angles "Cyberbullying" is predominant. The way of monitoring user opinions throughout social media platforms such as Twitter and Facebook have been proven to be an e ective way of learning practically all of the consumers' thoughts which can open the door of potential future implementations. General emotion inspection can give us important data. The examination of supposition on informal communities, for example, Twitter or Facebook, has become an amazing method for nding out about the clients' sentiments and has a wide scope of utilizations. Notwithstanding, the productivity furthermore, the exactness of notion examination is being blocked by the di culties experienced in characteristic language handling (NLP). As of late, it is established that profound learning models are potential answers to the drawbacks of NLP. Natural language processing refers to a process that enables the machine to act like human and decreases the space between the person and the machine. Thus, NLP readily communicates with the computer in a straightforward sense. NLP has gained several uses in recent times. Each one of them are extremely e ective in daily life. An example can be a device which can be handled by voice commands. Several research workers are putting e ort on this idea in order to make even more real-life applications Natural Language Processing has tremendous potential to facilitate the use of computer interfaces for humans, as people will ideally communicate in their own language to the computer instead of learning an exclusive language based on computer instructions. In case of programming, traditional programming language's importance has always been underrated. This concept is questionable. We believe that modern Natural Language Processing techniques can make possible the use of natural language to express programming ideas, thus drastically increasing the accessibility of programming to non-expert users. Our team thinks that the implementation of natural language to convey programming concepts may be made possible by contemporary natural language processing techniques so that programming is accessible to inexperienced consumers substantially. The following paper surveys the most recent analysis that have utilized profound methodology how to take care of conclusion investigation issues, for example, assessment extremity. Models utilizing term recurrence opposite record recurrence (TF-IDF) and content insertion was implemented to an arrangement of datasets. At last, one similar examination of the exploratory outcomes was carried out in respect to several models and information highlights.en_US
dc.description.statementofresponsibilityKazi Minhazul Islam
dc.description.statementofresponsibilityMd. Safkat Reza
dc.description.statementofresponsibilityMD. Samin Yeaser
dc.format.extent21 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectNLPen_US
dc.subjectDeep learningen_US
dc.subjectCyber bullyingen_US
dc.subjectRacismen_US
dc.subjectSocial mediaen_US
dc.subjectPredictionen_US
dc.subjectBi-directionalen_US
dc.subjectLSTMen_US
dc.subject.lcshMachine learning
dc.subject.lcshNatural language processing (Computer science)
dc.subject.lcshHuman-computer interaction
dc.titleSentiment analysis using Natural Language Processing (NLP) & deep learningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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