• 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