• DocumentCode
    1799807
  • Title

    A Study on Recursive Neural Network Based Sentiment Classification of Sina Weibo

  • Author

    Chen Fu ; Bai Xue ; Zhan Shaobin

  • Author_Institution
    Dept. of Comput., Beijing Foreign Studies Univ., Beijing, China
  • fYear
    2014
  • fDate
    24-26 Sept. 2014
  • Firstpage
    681
  • Lastpage
    685
  • Abstract
    Analyzing sentiment hidden in Sina Weibo´s huge amount of information can benefit online marketing, branding, customer relationship management and monitoring public opinions. In this paper, we show how a recursive neural network can be trained to classify Sina Weibo messages´ sentiment. Considering syntactic and semantic meaning of the sentence, this method is much superior to just basing on sentiment dictionary. Extensive experiments on huge dataset of Sina Weibo demonstrate that this model consistently outperforms existing sentiment classification model on identifying hidden or implied sentiment.
  • Keywords
    neural nets; social networking (online); Sina Weibo messages sentiment; branding; customer relationship management; online marketing; public opinion monitoring; recursive neural network; sentiment classification model; sentiment dictionary; Analytical models; Computational linguistics; Neural networks; Semantics; Support vector machine classification; Syntactics; Vectors; Word2vec; autoencoder; recursive neural network; sentiment analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Trust, Security and Privacy in Computing and Communications (TrustCom), 2014 IEEE 13th International Conference on
  • Conference_Location
    Beijing
  • Type

    conf

  • DOI
    10.1109/TrustCom.2014.88
  • Filename
    7011312