텍스트 마이닝과 기계 학습을 이용한 국내 가짜뉴스 예측
Fake News Detection for Korean News UsingText Mining and Machine Learning Techniques
- 발행
- 2018
- 소속·발행
- 국민대학교
- 출처
- 국내 KCI
- DOI
- 10.21219/jitam.2018.25.1.019
- 원문등록
- 2018-04-11
- 원문
- 원문 보기 ↗
개념
키워드
Fake News Detection, Korean News, Machine Learning, Text Mining, Fake News Detection, Korean News, Machine Learning, Text Mining
초록
Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news.
 In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, arti