Part I: State-of-the-art
Online Fake News Detection Using Machine Learning Techniques: A Systematic Mapping Study
Using Artificial Intelligence against the Phenomenon of Fake News: a Systematic Literature Review
Fake news detection in internet using deep learning: A review
Part II: Machine Learning Techniques and Fake News
Early Detection of Fake News from Social Media Networks using Computational Intelligence Approaches
Fandet Semantic Model: An OWL Ontology for Context-Based Fake News Detection on Social Media
Fake News Detection using Machine Learning and Natural Language Processing
Fake News Detection using Ensemble Learning and Machine Learning Algorithms
Evaluation of Machine Learning Methods for Fake News Detection
Credibility and Reliability News Evaluation Based on Artificial Intelligent Service with Feature Segmentation Searching and Dynamic Clustering
Deep Learning with Self-Attention Mechanism for Fake News Detection
Modeling and solving the fake news detection scheduling problem
Part III: Case Studies and Frameworks
The multiplier effect on the dissemination of false speeches on social networks: Experiment during the silly season in Spain
Detecting News Influence in a Country: One Step Forward Towards Understanding Fake News
Factors Affecting the Intention of Using Fintech Services in the Context of Combating of Fake News
Crowd Sourcing and Blockchain-based Incentive Mechanism to Combat Fake News
Framework for Fake News Classification using Vectorization and Machine Learning
Fact Checking: An Automatic end to end Fact Checking System
Part IV: Fake news and Covid-19 pandemic
False Information in a Post Covid-19 World
Applying Fuzzy Logic and Neural Network in Sentiment Analysis for fake news detection: Case of Covid-19
Analyzing Deep Learning Optimizers for COVID-19 Fake News Detection
Detecting Fake News On COVID-19 Vaccine from YouTube Videos Using Advanced Machine Learning Approaches.