Presentation 2021-11-26
Deep Learning Hybrid Models for Sentiment Analysis
Yunpeng Rong, Jun Ohkubo,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Sentiment analysis (SA), which can analyze the public attitudes towards various texts, has earned increasing attention from researchers. Recent research confirmed that deep learning models show great potential to accomplish the SA tasks because of their flexible structure. This research introduces a hybrid deep learning-based model named attention pooling-based dilated convolution neural network (APDCNN) for implementing the SA tasks. We also conducted experiments to compare its performance with some other previous models, whose results show that dilated operation enhances the performance of our hybrid model without increasing its computational complexity.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Sentiment analysisAttention poolingDilated convolution neural network
Paper # NC2021-30
Date of Issue 2021-11-19 (NC)

Conference Information
Committee NC / MBE
Conference Date 2021/11/26(1days)
Place (in Japanese) (See Japanese page)
Place (in English) Online
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Rieko Osu(Waseda Univ.) / Ryuhei Okuno(Setsunan Univ.)
Vice Chair Hiroshi Yamakawa(Univ of Tokyo) / Junichi Hori(Niigata Univ.)
Secretary Hiroshi Yamakawa(ATR) / Junichi Hori(NICT)
Assistant Nobuhiko Wagatsuma(Toho Univ.) / Tomoki Kurikawa(KMU) / Jun Akazawa(Meiji Univ. of Integrative Medicine) / Emi Yuda(Tohoku Univ)

Paper Information
Registration To Technical Committee on Neurocomputing / Technical Committee on ME and Bio Cybernetics
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Deep Learning Hybrid Models for Sentiment Analysis
Sub Title (in English)
Keyword(1) Sentiment analysisAttention poolingDilated convolution neural network
1st Author's Name Yunpeng Rong
1st Author's Affiliation Saitama University(Saitama Univ.)
2nd Author's Name Jun Ohkubo
2nd Author's Affiliation Saitama University(Saitama Univ.)
Date 2021-11-26
Paper # NC2021-30
Volume (vol) vol.121
Number (no) NC-271
Page pp.pp.13-17(NC),
#Pages 5
Date of Issue 2021-11-19 (NC)