NDLI: Chinese microblog sentiment classification based on convolution neural network with content extension method

Content Provider	IEEE Xplore Digital Library
Author	Xiao Sun Fei Gao Chengcheng Li Fuji Ren
Copyright Year	2015
Description	Author affiliation: IFLYTEK Co. Ltd., Hefei, China (Chengcheng Li) \|\| Tokushima Univ., Tokushima, Japan (Fuji Ren) \|\| Sch. of Comput. & Inf., Hefei Univ. of Technol., Hefei, China (Xiao Sun; Fei Gao)
Abstract	Related research for sentiment analysis on Chinese microblog is aiming at analyzing the emotion of posters. This paper presents a content extension method that combines post with its' comments into a microblog conversation for sentiment analysis. A new convolutional auto encoder which can extract contextual sentiment information from microblog conversation of the post is proposed. Furthermore, a DBN model, which is composed by several layers of RBM(Restricted Boltzmann Machine) stacked together, is implemented to extract some higher level feature for short text of a post. These RBM layers can encoder observed short text to learn hidden structures or semantics information for better feature representation. A ClassRBM (Classification RBM) layer, which is stacked on top of RBM layers, is adapted to achieve the final sentiment classification. The experiment results demonstrate that, with proper structure and parameter, the performance of the proposed deep learning method on sentiment classification is better than state-of-the-art surface learning models such as SVM or NB, which also proves that DBN is suitable for short-length document classification with the proposed feature dimensionality extension method.
Starting Page	408
Ending Page	414
File Size	4433816
Page Count	7
File Format	PDF
ISSN	21568111
e-ISBN	9781479999538
DOI	10.1109/ACII.2015.7344603
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-09-21
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Context Sentiment analysis Visualization Sentiment Analysis Data mining DBN Social Network Semantics Neural networks Feature extraction ClassRBM Microblog Conversation RBM
Content Type	Text
Resource Type	Article

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