Paper Abstract and Keywords |
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) |
Download PDF |
SC2022-15 |
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 |
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natural language processing |
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Twitter |
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sentiment analysis |
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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 |
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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 |
5 |
Date of Issue |
2022-05-20 (SC) |
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