DocumentCode
2234000
Title
Neural networks for sentiment analysis on Twitter
Author
Duncan, Brett ; Zhang, Yanqing
Author_Institution
Department of Computer Science, Georgia State University, Atlanta, 30302-5060, USA
fYear
2015
fDate
6-8 July 2015
Firstpage
275
Lastpage
278
Abstract
The online medium has become a significant way that people express their opinions online. Sentiment analysis can be used to find out the polarity of an opinion, such as positive, negative, or neutral. Sentiment analysis has applications such as companies getting their customer´s opinions on their products, political sentiment analysis, or opinions on movie reviews. Recent research has involved looking at text from online blogs, tweets, online movie reviews, etc. to try and classify the text as being positive, negative, or neutral. For this research, a feedforward neural network will be experimented with for sentiment analysis of tweets. The training set of tweets are collected using the Twitter API using positive and negative keywords. The testing set of tweets are collected using the same positive and negative keywords.
Keywords
Companies; Motion pictures; Training; feedforward pattern network; sentiment analysis; text classification;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics & Cognitive Computing (ICCI*CC), 2015 IEEE 14th International Conference on
Conference_Location
Beijing, China
Print_ISBN
978-1-4673-7289-3
Type
conf
DOI
10.1109/ICCI-CC.2015.7259397
Filename
7259397
Link To Document