- Volume 9 Issue 7
DOI QR Code
Inference of Korean Public Sentiment from Online News
온라인 뉴스에 대한 한국 대중의 감정 예측
- Matteson, Andrew Stuart (Dept. of Computer Science and Engineering, Korea University) ;
- Choi, Soon-Young (Dept. of Computer Science and Engineering, Korea University) ;
- Lim, Heui-Seok (Dept. of Computer Science and Engineering, Korea University)
- Received : 2018.04.25
- Accepted : 2018.07.20
- Published : 2018.07.28
Online news has replaced the traditional newspaper and has brought about a profound transformation in the way we access and share information. News websites have had the ability for users to post comments for quite some time, and some have also begun to crowdsource reactions to news articles. The field of sentiment analysis seeks to computationally model the emotions and reactions experienced when presented with text. In this work, we analyze more than 100,000 news articles over ten categories with five user-generated emotional annotations to determine whether or not these reactions have a mathematical correlation to the news body text and propose a simple sentiment analysis algorithm that requires minimal preprocessing and no machine learning. We show that it is effective even for a morphologically complex language like Korean.
Supported by : National Research Foundation of Korea (NRF)
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