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dc.contributor.advisorAli, Md. Haider
dc.contributor.authorHossain, Mohammad Samman
dc.contributor.authorJui, Israt Jahan
dc.contributor.authorSuzana, Afia Zahin
dc.date.accessioned2017-06-19T05:59:57Z
dc.date.available2017-06-19T05:59:57Z
dc.date.copyright2017
dc.date.issued2017
dc.identifier.otherID 13301040
dc.identifier.otherID 13301120
dc.identifier.otherID 13101289
dc.identifier.urihttp://hdl.handle.net/10361/8246
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2017.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 35 - 37).
dc.description.abstractIn this project, we propose a system that assigns scores indicating positive or negative to newspaper headlines. Many works have been done on sentiment analysis, document clustering for newspaper headlines in English. We are going to do the same for Bengali language. News headlines from one Bengali newspaper [1] is used for the purpose of the project. As there is no dataset of headlines for this newspaper, we are using web crawler to get necessary headlines to make a dataset to use for this project. For our proposed system, a number of classifiers will be used such as Support Vector Machine [2], Logistic Regression [17] etc. Through the experiments, our aim is to establish a system, which can identify positive and negative news accurately.en_US
dc.description.statementofresponsibilityMohammad Samman Hossain
dc.description.statementofresponsibilityIsrat Jahan Jui
dc.description.statementofresponsibilityAfia Zahin Suzana
dc.format.extent37 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis 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.subjectSentiment analysisen_US
dc.subjectSVMen_US
dc.subjectBoosted treeen_US
dc.subjectLogisticen_US
dc.subjectBengalien_US
dc.subjectClassifiersen_US
dc.titleSentiment analysis for Bengali newspaper headlinesen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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