Fake news detection algorithm based on incorporating multi-level features
Abstract
References
Index Terms
- Fake news detection algorithm based on incorporating multi-level features
Recommendations
Extracting Common Features of Fake News by Multi-Head-Attention
Security and Privacy in Social Networks and Big DataAbstractSeveral methods for detecting fake news using machine learning have been proposed. Previous studies have only focused on a limited dataset, and few researchers have proposed versatile models that can be applied to various fields. In this study, we ...
Multidimensional Analysis of Fake News Spreaders on Twitter
Computational Data and Social NetworksAbstractSocial media has become a tool to spread false information with the help of its large complex network. The consequences of such misinformation could be very severe. The paper uses the Twitter conversations about the scrapping of Article 370 in ...
A survey on fake news and rumour detection techniques
AbstractFalse or unverified information spreads just like accurate information on the web, thus possibly going viral and influencing the public opinion and its decisions. Fake news and rumours represent the most popular forms of false and ...
Comments
Information & Contributors
Information
Published In
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Funding Sources
- Haikou Key Science and Technology Project
- the National Natural Science Foundation of China
- Hainan Key Science and Technology Project
Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 49Total Downloads
- Downloads (Last 12 months)49
- Downloads (Last 6 weeks)3
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format