In this project I have created a fake news classifier based on the news title and author and got an 99.46% accuracy.

A fact checking DApp which verifies the authenticity of news.

fake news detection using passive Aggresive classifier

Links to conference/journal publications in automated fact-checking (resources for the TACL22/EMNLP23 paper).

Paper list of misinformation research using (multi-modal) large language models, i.e., (M)LLMs.

This project involves an extensive exploration of fake news detection using machine learning techniques. It encompasses data preprocessing, feature extraction, model training, and evaluation to classify news articles as real or fake. Through thorough analysis and model validation, the project aims to provide valuable insights into the effectiveness

Bengali/Bangla Fake Review Detection Dataset

Fake News Detection

Exploring the Dual Role of AI: RNNs and BERT for Fake News Detection and LLMs for Fake News Generation

AntiFa (Anti FakeNews) é um projeto dedicado a analisar e quantificar a porcentagem de notícias falsas (fake news) disseminadas por políticos e personalidades brasileiras em suas redes sociais.

Fake news detection using TF-IDF vectorization and LinearSVC

Official repository for "Zoom Out and Observe: News Environment Perception for Fake News Detection", ACL 2022.

FNDetectoApp

📄 Unbiased disinformation analyzer. Measure the deviance of fake information from the truth.

The source code of "Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks

[SIGIR 2022] Source code and datasets for "Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention".

[WWW 2022] The source code of "Evidence-aware Fake News Detection with Graph Neural Networks"

Submission for SemEval 2024 - Task 8 (Subtask A)

Official repository for "Bad Actor, Good Advisor: Exploring the Role of Large Language Models in Fake News Detection", AAAI 2024.