dc.contributor.advisor | Suraiya Tairin | |
dc.contributor.author | Neha, Maheen Absar | |
dc.contributor.author | Rahman, Md. Intisher | |
dc.contributor.author | Nuzhat, Mahpara | |
dc.contributor.author | Zereen, Sifat | |
dc.date.accessioned | 2018-01-04T03:38:44Z | |
dc.date.available | 2018-01-04T03:38:44Z | |
dc.date.copyright | 2017 | |
dc.date.issued | 2017-08 | |
dc.identifier.issn | ID 14141003 | |
dc.identifier.other | ID 13241007 | |
dc.identifier.other | ID 16341013 | |
dc.identifier.other | ID 13201012 | |
dc.identifier.uri | http://hdl.handle.net/10361/8907 | |
dc.description | This 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.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 54-55). | |
dc.description.abstract | As 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.statementofresponsibility | Maheen Absar Neha | |
dc.description.statementofresponsibility | Md. Intisher Rahman | |
dc.description.statementofresponsibility | Mahpara Nuzhat | |
dc.description.statementofresponsibility | Sifat Zereen | |
dc.format.extent | 55 pages | |
dc.language.iso | en | en_US |
dc.publisher | BRAC University | en_US |
dc.rights | BRAC 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.subject | Twitter | en_US |
dc.subject | Statistica | en_US |
dc.subject | Hashtags | en_US |
dc.subject | Tweet | en_US |
dc.subject | Data mining | en_US |
dc.subject | Text mining | en_US |
dc.title | Evaluating user influence in Twitter based on hashtags using data mining | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, BRAC University | |
dc.description.degree | B. Computer Science and Engineering
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