Show simple item record

dc.contributor.advisorSuraiya Tairin
dc.contributor.authorNeha, Maheen Absar
dc.contributor.authorRahman, Md. Intisher
dc.contributor.authorNuzhat, Mahpara
dc.contributor.authorZereen, Sifat
dc.date.accessioned2018-01-04T03:38:44Z
dc.date.available2018-01-04T03:38:44Z
dc.date.copyright2017
dc.date.issued2017-08
dc.identifier.issnID 14141003
dc.identifier.otherID 13241007
dc.identifier.otherID 16341013
dc.identifier.otherID 13201012
dc.identifier.urihttp://hdl.handle.net/10361/8907
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 54-55).
dc.description.abstractAs more and more data is being processed and generated every day, it has become a tremendous challenge to process and analyze. Big data analysis is a process of collecting, organizing and analyzing large sets of data to discover patterns and other useful information. It can help understand the information contained within data using specialized tools and applications for predictive analysis, data mining, text mining, forecasting and data optimization. We will be working with data from the most popular microblogging platform, Twitter, to study the social issues concerning various forms of harassment. Twitter users categorize status messages (Tweets) using hashtags, which are also used for searching specific topics or events. We can determine trends in Twitter-documented bullying among different demographics by analyzing the hashtags which represent different forms of social attacks, incidents of oppression, discrimination and cultural persecution. Out of the several tools used worldwide to interpret datasets, we will be using an advanced data mining tool called STATISTICA.en_US
dc.description.statementofresponsibilityMaheen Absar Neha
dc.description.statementofresponsibilityMd. Intisher Rahman
dc.description.statementofresponsibilityMahpara Nuzhat
dc.description.statementofresponsibilitySifat Zereen
dc.format.extent55 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.subjectTwitteren_US
dc.subjectStatisticaen_US
dc.subjectHashtagsen_US
dc.subjectTweeten_US
dc.subjectData miningen_US
dc.subjectText miningen_US
dc.titleEvaluating user influence in Twitter based on hashtags using data miningen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering 


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record