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  • 标题:ONLINE FAKE NEWS DETECTION ALGORITHM
  • 本地全文:下载
  • 作者:SAKEENA M. SIRAJUDEEN ; NUR FATIHAH A. AZMI ; ADAMU I. ABUBAKAR
  • 期刊名称:Journal of Theoretical and Applied Information Technology
  • 印刷版ISSN:1992-8645
  • 电子版ISSN:1817-3195
  • 出版年度:2017
  • 卷号:95
  • 期号:17
  • 页码:4114
  • 出版社:Journal of Theoretical and Applied
  • 摘要:The widespread of online hoax news is increasing rapidly, especially with the vast number of Microblogging sites allowing disseminating distasteful content. This has become vigorous and nearly unstoppable now. Spreading online fake news has been identified as one of the major top concern of online abuse. Due to the difficulty in preventing and evaluating what does fake news contain prior to publishing it online, if an algorithm is known for detecting fake news, then spreading online fake news wouldn�t exist in the first place, lead this paper to presents an evaluation of the effectiveness of algorithm(s), able to detect and filter to reasonable degree of accuracy what constitute an online fake news. The proposed approach is a multi-layered evaluations technique to be built as an app, where all information read online is associated with a tag, given a description of the facts about the contain. A proof of concept is provided for better understanding of the proposed techniques. This has contributed in providing possible steps to be taken by some popular Microblogging sites to stop the widespread of fake news.
  • 关键词:Online Fake News; Hoax News; Detection; Filtering
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