Machine Learning Approach to Detect Fake News, Misinformation in COVID-19 Pandemic

被引:3
|
作者
Bojjireddy, Sirisha [1 ]
Chun, Soon Ae [2 ]
Geller, James [1 ]
机构
[1] New Jersey Inst Technol, Newark, NJ 07102 USA
[2] CUNY Coll Staten Isl, Staten Isl, NY USA
来源
PROCEEDINGS OF THE 22ND ANNUAL INTERNATIONAL CONFERENCE ON DIGITAL GOVERNMENT RESEARCH, DGO 2021 | 2021年
关键词
Fake news; misinformation; machine learning; Covid-19;
D O I
10.1145/3463677.3463762
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Fake news is false information about current events, intentionally created to mislead readers. The spread of such fake news has the potential to create a negative impact on individuals and society. With today's straightforward creation of social media posts, there has been an increasing amount of fake news, compared to traditional media in the past. We present one of the most serious societal issue of misinformation, specifically using Presidential Election and COVID-19 health related fake news. We present multi-dimensional approaches that organizations and individuals could utilize for detecting fake news, ranging from human/social approaches, to technical approaches to organizational trust/policy approaches. The Machine Learning approach as a technical solution is presented for automating the detection of fake news and misleading contents. A fake news detection web application is presented to make it easy for end users to determine whether an article is legitimate or fake.
引用
收藏
页码:575 / 578
页数:4
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