데이터 마이닝을 활용한 가짜뉴스의 선제적 대응을 위한 연구 : M 온라인 커뮤니티 게시물을 중심으로
A Study on the Preemptive Measure for Fake News Eradication Using Data Mining Algorithms :Focused on the M Online Community Postings
- 발행
- 2019 등록이 논문은 발행 시점을 확인하지 못해 원문 등록일을 적었습니다. KCI가 2005~2008년에 옛 논문을 몰아서 올린 탓에, 그 시기 등록분은 발행보다 평균 3~5년 늦습니다. 실제 발행연도는 더 이를 수 있습니다.
- 소속·발행
- 호서대학교
- 출처
- 국내 KCI
- 원문
- 원문 보기 ↗
개념
키워드
Fake News Preempive Measure, Misinformation, Online Community, Fake News Preempive Measure, Misinformation, Online Community
초록
Fake news threaten democratic elections and causes social conflicts, resulting in major damage. However, the concept of fake news is hard to define, as there is a saying, "News is not fake, fake is not news." Fake news, however, has irreversible characteristics that can not be recovered or reversed completely through post-punishment of economic and political benefits. It is also rapidly spreading in the early days. Therefore, it is very important to preemptively detect these types of articles and prevent their blind proliferation. The existing countermeasures are focused on reporting fake news, raising the level of punishment, and the media & academia to determine the authenticity of the news. Researchers are also trying to determine the authenticity by analyzing its contents. Apart from the contents of fake news, determining the behavioral characteristics of the promoters and its qualities can help identify the possibility of having fake news in advance. The online community has a fake news interception and response tradition through its long-standing community-based activities. As a result, I attempted to model the fake news by analyzing the affirmation-denial analysis and po