Dimensional Sentiment Analysis of Korean Text using Data Balancing

Title
Dimensional Sentiment Analysis of Korean Text using Data Balancing
Authors
김창환전태희
Keywords
차원적 감성 분석; 감정 회귀; 한국어 텍스트; 데이터 분포; 데이터 균형화
Issue Date
2021-07
Publisher
정보과학회논문지
Citation
VOL 48, NO 7-801
Abstract
Compared with most studies on categorical sentiment analysis which aims to represent emotional states as a small set of emotion categories, there have been fewer studies on dimensional sentiment analysis which treats sentiment analysis as a regression problem because of the shortage of data. Recently, the National Information Society Agency (NIA) released open data, Multimodal Video Data, through their web site, AI Hub. Using this data, we experimented with dimensional sentiment analysis of Korean text. For this purpose, we used CNN which is one of the conventional deep learning models in NLP. We also verified that data balancing could improve the performance of models. The results show that the model trained on Multimodal Video Data performs well enough to show that the data should be useful for dimensional sentiment analysis of Korean text and that with data balancing the model can perform better in spite of their fewer training data.
URI
http://pubs.kist.re.kr/handle/201004/73584
ISSN
2383-6296
Appears in Collections:
KIST Publication > Article
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

BROWSE