Fake News Detection: A Comprehensive Survey
- Resource Type
- Conference
- Authors
- Tata, Elton; Ajdari, Jaumin; Besimi, Nuhi
- Source
- 2023 46th MIPRO ICT and Electronics Convention (MIPRO) ICT and Electronics Convention (MIPRO), 2023 46th MIPRO. :309-314 May, 2023
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Support vector machines
Surveys
Visualization
Systematics
Recurrent neural networks
Social networking (online)
Biological system modeling
fake news
machine learning
deep learning
- Language
- ISSN
- 2623-8764
The growth and increasing use of digital information platforms have dramatically changed the way news is produced, disseminated, and consumed in our society. Fake news can be found everywhere through popular platforms like social media and the internet. Efforts to develop an effective system for identifying fake news are numerous. Artificial intelligent tools are included to address this difficult issue. Fake news appears in different forms based on the features of their content. The aim of this research is to provide a comprehensive understanding of the various techniques within the domain of fake news detection through a systematic literature review of the existing work. This literature will demonstrate the most significant and relevant models to provide orientations in future research.