Political Opinion Mining from Article Comments using Deep Learning (딥러닝을 활용한 정치 기사 댓글 분석)

Dae-Kyung Sung (성대경); Young-Seob Jeong (정영섭)

doi:10.9708/jksci.2018.23.01.009

Political Opinion Mining from Article Comments using Deep Learning

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2018, 23(1), pp.9-15
DOI : 10.9708/jksci.2018.23.01.009
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : November 1, 2017
Accepted : January 2, 2018
Published : January 31, 2018

Dae-Kyung Sung ¹, Young-Seob Jeong ²

¹경북대학교
²순천향대학교

Accredited

ABSTRACT

Policy polls, which investigate the degree of support that the policy　has for policy implementation, play an important role in making decisions. As the number of Internet users increases, the public is actively commenting on their policy news stories.　Current policy polls tend to rely heavily on phone and offline surveys. Collecting and analyzing policy articles is useful in policy surveys.　In this study, we propose a method of analyzing comments using deep learning technology showing outstanding performance in various fields. In particular, we designed various models based on the recurrent neural network (RNN) which is suitable for sequential data and compared the performance with the support vector machine (SVM), which is a traditional machine learning model. 　For all test sets, the SVM model show an accuracy of 0.73 and the RNN model have an accuracy of 0.83.

KEYWORDS

recurrent neural network, opinion mining, semantic analysis

Citation status

* References for papers published after 2023 are currently being built.

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This paper was written with support from the National Research Foundation of Korea.

KJCKorea
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Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Political Opinion Mining from Article Comments using Deep Learning

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* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Political Opinion Mining from Article Comments using Deep Learning

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* References for papers published after 2023 are currently being built.