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Paper Abstract and Keywords
Presentation 2019-06-21 15:40
Semi-Automatic Labeling for Emotion Classification with Deep Learning
Kyosuke Masuda, Hiromitsu Nishizaki (Univ. of Yamanashi) NLC2019-5
Abstract (in Japanese) (See Japanese page) 
(in English) We previously considered that the emotional classification method based on deep learning for tweets on social networking service Twitter. In the case of using the deep learning (machine learning) framework for emotion classification, we have to prepare a large emotion corpus in which each sentence has emotion label(s). However, it high costs to construct the emotion corpus. Therefore, we have semi-automatically constructed the emotion corpus from Twitter using some seed emotion words which were selected from the emotion dictionary, in which the emotion words are well-defined. Tweets were retrieved by one seed emotion word and the retrieved texts were attached the emotion label(s) based on the emotion category of the seed word. However, the deep learning-based emotion classification model could not achieve the high-accurate emotion classification because the semi-automatically constructed corpus had a lot of errors of emotion labels. In this paper, therefore, we propose a method for improving the quality of the emotion labels by automatically correcting the errors of emotion labels. The experimental result showed that the our proposed method worked well and the classification accuracy was improved to 63.8% from the 55.1% on the Twitter emotion classification task.
Keyword (in Japanese) (See Japanese page) 
(in English) Deep learning / emotion recognition / Iteration training / automatic label correction / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 98, NLC2019-5, pp. 29-33, June 2019.
Paper # NLC2019-5 
Date of Issue 2019-06-14 (NLC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee NLC IPSJ-ICS  
Conference Date 2019-06-21 - 2019-06-22 
Place (in Japanese) (See Japanese page) 
Place (in English) Hiroshima University of Economics (Tatemachi Campus) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Application of natural language processing and intelligent systems, and general topic of NLP 
Paper Information
Registration To NLC 
Conference Code 2019-06-NLC-ICS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Semi-Automatic Labeling for Emotion Classification with Deep Learning 
Sub Title (in English)  
Keyword(1) Deep learning  
Keyword(2) emotion recognition  
Keyword(3) Iteration training  
Keyword(4) automatic label correction  
1st Author's Name Kyosuke Masuda  
1st Author's Affiliation University of Ymanashi (Univ. of Yamanashi)
2nd Author's Name Hiromitsu Nishizaki  
2nd Author's Affiliation University of Ymanashi (Univ. of Yamanashi)
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Date Time 2019-06-21 15:40:00 
Presentation Time 25 
Registration for NLC 
Paper # IEICE-NLC2019-5 
Volume (vol) IEICE-119 
Number (no) no.98 
Page pp.29-33 
#Pages IEICE-5 
Date of Issue IEICE-NLC-2019-06-14 

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