Awesome-Misinformation-Detection

Introduction

This is a curated collection of resources on Misinformation Detection, covering the latest research papers, code implementations, and datasets in related fields such as fake news detection, deepfake detection, and rumor detection. This project aims to provide researchers and practitioners with a comprehensive resource guide to quickly understand and learn about the latest advances in misinformation detection.

This project is organized by different detection tasks and data types, including but not limited to:

• Fake News Detection: Methods for identifying fake news based on text, images, and multimodal approaches
• Deepfake Detection: Detection techniques for AI-generated images and videos
• Rumor Detection: Identification and analysis of rumor propagation on social media

Contributions of excellent papers, code, and datasets are welcome!

Fake News Detection

Paper Name	Code	Source
Synergizing LLMs with Global Label Propagation for Multimodal Fake News Detection	Source	Code
TripleFact: Defending Data Contamination in the Evaluation of LLM-driven Fake News Detection	Source	Code
PCoT: Persuasion-Augmented Chain of Thought for Detecting Fake News and Social Media Disinformation	Source	Code
Detection of Human and Machine-Authored Fake News in Urdu	Source
Generate First, Then Sample: Enhancing Fake News Detection with LLM-Augmented Reinforced Sampling	Source
IMOL: Incomplete-Modality-Tolerant Learning for Multi-Domain Fake News Video Detection	Source

Deepfake Detection

Name	Code	Source
SpeechFake: A Large-Scale Multilingual Speech Deepfake Dataset Incorporating Cutting-Edge Generation Methods	Source	Code

Rumor Detection

Name	Code	Source
SINCon: Mitigate LLM-Generated Malicious Message Injection Attack for Rumor Detection	Source
LLM-based Rumor Detection via Influence Guided Sample Selection and Game-based Perspective Analysis	Source