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 :
بازگشت