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