Predicting stock market trend from twitter feed and building a framework for Bangladesh
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018.
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| Լեզու: | English |
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BRAC University
2018
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| Առցանց հասանելիություն: | http://hdl.handle.net/10361/10153 |
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10361-101532022-01-26T10:10:33Z Predicting stock market trend from twitter feed and building a framework for Bangladesh Karim, Shabab Abdullah, Tahmid Tayaba, Umme Majumdar, Mahbub Alam Department of Computer Science and Engineering, BRAC University Stock market Sentiment analysis Classi er Regression Machine learning Logistic regression Tweets This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. Cataloged from PDF version of thesis. Includes bibliographical references (pages 45-47). Social media has become an integral part in our day to day lives. What we share in these media are what we believe in and give others a window of opportunity to predict what is going on in our mind or how our actions will be in the future. Twitter is amazing at this job because usually people tend to write exactly what they are thinking when the character limit is only hundred and forty characters. This is particularly helpful when we want to analyze the trends of stock market. In this thesis paper, we tried to come up with a solution to better predict stock market trends analyzing the sentiments from twitter feeds obtained from StockTwits. Shabab Karim Tahmid Abdullah Umme Tayaba B. Computer Science and Engineering 2018-05-15T06:46:06Z 2018-05-15T06:46:06Z 2018 2018-04 Thesis ID 14101138 ID 14101142 ID 14101034 http://hdl.handle.net/10361/10153 en BRAC 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. 47 pages application/pdf BRAC University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
Stock market Sentiment analysis Classi er Regression Machine learning Logistic regression Tweets |
| spellingShingle |
Stock market Sentiment analysis Classi er Regression Machine learning Logistic regression Tweets Karim, Shabab Abdullah, Tahmid Tayaba, Umme Predicting stock market trend from twitter feed and building a framework for Bangladesh |
| description |
This thesis is submitted in partial fulfilment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2018. |
| author2 |
Majumdar, Mahbub Alam |
| author_facet |
Majumdar, Mahbub Alam Karim, Shabab Abdullah, Tahmid Tayaba, Umme |
| format |
Thesis |
| author |
Karim, Shabab Abdullah, Tahmid Tayaba, Umme |
| author_sort |
Karim, Shabab |
| title |
Predicting stock market trend from twitter feed and building a framework for Bangladesh |
| title_short |
Predicting stock market trend from twitter feed and building a framework for Bangladesh |
| title_full |
Predicting stock market trend from twitter feed and building a framework for Bangladesh |
| title_fullStr |
Predicting stock market trend from twitter feed and building a framework for Bangladesh |
| title_full_unstemmed |
Predicting stock market trend from twitter feed and building a framework for Bangladesh |
| title_sort |
predicting stock market trend from twitter feed and building a framework for bangladesh |
| publisher |
BRAC University |
| publishDate |
2018 |
| url |
http://hdl.handle.net/10361/10153 |
| work_keys_str_mv |
AT karimshabab predictingstockmarkettrendfromtwitterfeedandbuildingaframeworkforbangladesh AT abdullahtahmid predictingstockmarkettrendfromtwitterfeedandbuildingaframeworkforbangladesh AT tayabaumme predictingstockmarkettrendfromtwitterfeedandbuildingaframeworkforbangladesh |
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