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Presentation 2022-05-27 15:31
[Poster Presentation] Performance Evaluation of Twitter Classification on Pre-Trained Model by Word Embeddings
Haruki Kimura, Incheon Paik (UoA) SC2022-15
Abstract (in Japanese) (See Japanese page) 
(in English) The Internet is used as social infrastructure to such an extent that modern society would not be possible without it. With the development of the Internet, various data has been accumulated on the Web. What I would like to focus on here are social networking services. Today, we live in an age where everyone can send out information, and the information sent out by individuals on SNS contains a variety of emotions. If we can analyze this information, we can apply it to various things. We will use the data collected from Twitter to analyze emotions. In 2018, a natural language processing model called BERT was released by Google. A previous study compared BERT with earlier methods and showed that BERT effectively analyzes Twitter sentiment.
In this study, we use a model that has already been pre-trained and compare the accuracy by changing the batch size and data size. As a result, we were able to get better results than the previous study by reducing the batch size and data size.
Keyword (in Japanese) (See Japanese page) 
(in English) natural language processing / Twitter / sentiment analysis / BERT / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 50, SC2022-15, pp. 88-92, May 2022.
Paper # SC2022-15 
Date of Issue 2022-05-20 (SC) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction
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. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee SC  
Conference Date 2022-05-27 - 2022-05-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) AI Service and Digital Transformation, and general topics 
Paper Information
Registration To SC 
Conference Code 2022-05-SC 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance Evaluation of Twitter Classification on Pre-Trained Model by Word Embeddings 
Sub Title (in English)  
Keyword(1) natural language processing  
Keyword(2) Twitter  
Keyword(3) sentiment analysis  
Keyword(4) BERT  
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1st Author's Name Haruki Kimura  
1st Author's Affiliation University of Aizu (UoA)
2nd Author's Name Incheon Paik  
2nd Author's Affiliation University of Aizu (UoA)
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Speaker Author-1 
Date Time 2022-05-27 15:31:00 
Presentation Time 3 minutes 
Registration for SC 
Paper # SC2022-15 
Volume (vol) vol.122 
Number (no) no.50 
Page pp.88-92 
#Pages
Date of Issue 2022-05-20 (SC) 


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