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dc.contributor.advisorAlam, Md.Golam Rabiul
dc.contributor.authorToma, Syeda Tanzina Farhin
dc.contributor.authorBhuiyan, Shahan Jamil
dc.contributor.authorDawood, Tahmid
dc.contributor.authorSaha, Chandan Kumar
dc.date.accessioned2020-12-20T08:33:22Z
dc.date.available2020-12-20T08:33:22Z
dc.date.copyright2019
dc.date.issued2019-12
dc.identifier.otherID 16101003
dc.identifier.otherID 16101091
dc.identifier.otherID 16101105
dc.identifier.otherID 13101147
dc.identifier.urihttp://hdl.handle.net/10361/14091
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2019.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 93-95).
dc.description.abstractMarketing strategy is being a new challenge in this modern era. Along with the global market, people's choices are also changing so to grab the focus of buyers, organizations are making changes in their marketing policy based on user's choice to increase the possibility of their product being sold. Advertisements are the way to promote products and they are available on every media platform nowadays. The focus was always to gather public attention through different messages but which factors of advertising were needed more was not fixed. To recognize the dependencies of a successful advertisement and identify the factors which create good impression in people mind we lead this study. Using supervised machine learning algorithms and feature extraction method we find out the factors of ad liking and predict the purchase intent through emotionomics which makes an ad successful.en_US
dc.description.statementofresponsibilitySyeda Tanzina Farhin Toma
dc.description.statementofresponsibilityShahan Jamil Bhuiyan
dc.description.statementofresponsibilityTahmid Dawood
dc.description.statementofresponsibilityChandan Kumar Saha
dc.format.extent95 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.subjectFactor analysisen_US
dc.subjectAdvertisementsen_US
dc.subjectEEGen_US
dc.subjectEmotionomicsen_US
dc.titleFactor analysis of ad liking and prediction of purchase intent through emotionomicsen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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