Sentiment analysis of big social data with Apache Hadoop
| dc.contributor.author | Kang, Qiuling | |
| dc.date.accessioned | 2015-10-02T20:47:29Z | |
| dc.date.available | 2015-10-02T20:47:29Z | |
| dc.date.issued | 2014-12 | |
| dc.description.abstract | Twitter is a microblog service and is a very popular communication mechanism. Users of Twitter express their interests, favorites, and sentiments towards various topics and issues they encountered in daily life, therefore, Twitter is an important online platform for people to express their opinions which is a key fact to influence their behaviors. Thus, sentiment analysis for Twitter data is meaningful for both individuals and organizations to make decisions. Due to the huge amount of data generated by Twitter every day, a system which can store and process big data is becoming a problem. In this study, we present a method to collect Twitter data sets, and store and analyze the data sets on Hadoop platform. The experiment results prove that the present method performs efficient. | |
| dc.description.degree | M.S. | |
| dc.identifier.uri | http://hdl.handle.net/10125/101227 | |
| dc.language | eng | |
| dc.publisher | University of Hawaii at Manoa | |
| dc.relation | Theses for the degree of Master of Science (University of Hawaii at Manoa). Electrical Engineering. | |
| dc.rights | All UHM dissertations and 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 from the copyright owner. | |
| dc.subject | Twitter data sets | |
| dc.subject | big data | |
| dc.title | Sentiment analysis of big social data with Apache Hadoop | |
| dc.type | Thesis | |
| dc.type.dcmi | Text |