mihail911/fake-news
Building a fake news detector from initial ideation to model deployment
This project offers a comprehensive guide and tools to build a system that identifies fake news. It takes news articles or text snippets as input and determines their likelihood of being fake, providing a score or label. Media analysts, journalists, and content moderators can use this to assess information credibility.
167 stars.
Use this if you need to develop, understand, and deploy a custom system for detecting misinformation in text.
Not ideal if you are looking for an off-the-shelf, ready-to-use fake news detection application without building it yourself.
Stars
167
Forks
64
Language
Jupyter Notebook
License
AGPL-3.0
Category
Last pushed
Feb 15, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/mihail911/fake-news"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
google-research/fool-me-twice
Game code and data for Fool Me Twice: Entailment from Wikipedia Gamification...
FakeNewsChallenge/fnc-1-baseline
A baseline implementation for FNC-1
palewire/storysniffer
Inspect a URL and estimate if it contains a news story
IKMLab/CFEVER-data
AAAI-24 CFEVER: A Chinese Fact Extraction and VERification Dataset
pmacinec/fake-news-datasets
This repository contains list of available fake news datasets for data mining.