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dc.contributor.advisorAshraf, Faisal Bin
dc.contributor.authorKhan, Farden Ehsan
dc.contributor.authorRuhan, Ahmed Mahir
dc.contributor.authorShamsuddin, Rifat
dc.date.accessioned2023-10-15T07:03:05Z
dc.date.available2023-10-15T07:03:05Z
dc.date.copyright©2022
dc.date.issued2022-09-29
dc.identifier.otherID 19101418
dc.identifier.otherID 19101330
dc.identifier.otherID 19101336
dc.identifier.urihttp://hdl.handle.net/10361/21814
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 37-38).
dc.description.abstractIn recent times, social media usage has reached such heights that it has become a powerhouse in producing trends, bringing such topics that would have remained outside of popular consciousness. Our goal is to analyze how the success of products such as movies can be affected by people’s shared thoughts and reactions about it on social media. From the data extracted from social media comments, we will study the sentiment of people regarding a certain movie. For our research, the work will be based on unreleased movies and predict the outcome after release. Accumulated reviews about a movie will be analyzed to decipher whether the public sentiment is positive or negative towards it and estimate the willingness to buy a specific film. From this we will find the correlation between how positive and negative attention can affect the success of a production.en_US
dc.description.statementofresponsibilityFarden Ehsan Khan
dc.description.statementofresponsibilityAhmed Mahir Ruhan
dc.description.statementofresponsibilityRifat Shamsuddin
dc.format.extent48 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.subjectSocial mediaen_US
dc.subjectTrend analysisen_US
dc.subjectDeep learningen_US
dc.subjectSentiment analysisen_US
dc.subjectKNNen_US
dc.subjectText miningen_US
dc.subjectMLPen_US
dc.subjectRoBERTaen_US
dc.subjectRandom foresten_US
dc.subjectBARTen_US
dc.subjectDecision Treeen_US
dc.subjectDistilBERTen_US
dc.subject.lcshSocial media--Economic aspects
dc.subject.lcshMachine learning
dc.titleSocial media trend analysis to predict the success of products using deep learning techniqueen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB.Sc. in Computer Science


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