dc.contributor.advisor | Majumdar, Dr. Mahbub Alam | |
dc.contributor.author | Chakraborty, Pranjal | |
dc.contributor.author | Rony, Rashad Al Hasan | |
dc.contributor.author | Pria, Ummay Sani | |
dc.date.accessioned | 2017-05-30T06:46:11Z | |
dc.date.available | 2017-05-30T06:46:11Z | |
dc.date.copyright | 2017 | |
dc.date.issued | 4/16/2017 | |
dc.identifier.other | ID 13301071 | |
dc.identifier.other | ID 13301033 | |
dc.identifier.other | ID 13301055 | |
dc.identifier.uri | http://hdl.handle.net/10361/8206 | |
dc.description | Cataloged from PDF version of thesis report. | |
dc.description | Includes bibliographical references (page 36-37). | |
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.abstract | Collecting opinions of mass people through the social networking sites has become easy and handy now-a-days. These opinions show the sentimental state of a large number of people, which, according to behavioral economics, will give us the idea about their decision-making process. Twitter is a very popular social networking site and by opinion mining, it is possible to get the sentimental state from the tweets. Moreover, there are publicly available data of Twitter. In this thesis paper, we will try to correlate between this sentimental data and stock market data to predict future movement of stock market. | en_US |
dc.description.statementofresponsibility | Pranjal Chakraborty | |
dc.description.statementofresponsibility | Rashad Al Hasan Rony | |
dc.description.statementofresponsibility | Ummay Sani Pria | |
dc.format.extent | 37 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 | Stock market | en_US |
dc.subject | Twitter feed | en_US |
dc.subject | Sentiment analysis | en_US |
dc.subject | Decision tree | en_US |
dc.subject | Random forest | en_US |
dc.subject | Boosted tree | en_US |
dc.subject | Opinion mining | en_US |
dc.subject | Machine Learning | en_US |
dc.title | Predicting stock market movement using sentiment analysis of twitter feed | 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 | |