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온라인 뉴스에 대한 한국 대중의 감정 예측Inference of Korean Public Sentiment from Online News
- Other Titles
- Inference of Korean Public Sentiment from Online News
- Authors
- Andrew Stuart Matteson; 최순영; 임희석
- Issue Date
- 2018
- Publisher
- 한국융합학회
- Keywords
- 감정분석; 크라우드소싱; 온라인뉴스; 감정사전; 사회적 감정 탐지; 자연어처리; Sentiment Analysis; Crowdsourcing; Online News; Emotion Dictionary; Social Emotion Detection; Natural Language Processing
- Citation
- 한국융합학회논문지, v.9, no.7, pp.25 - 31
- Indexed
- KCI
- Journal Title
- 한국융합학회논문지
- Volume
- 9
- Number
- 7
- Start Page
- 25
- End Page
- 31
- ISSN
- 2233-4890
- Abstract
- 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.
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