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
Link To Document :
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