A public event calendar about trust, verification, fact checking & beyond, curated by the MisinfoCon community

Deep Classiflie is a framework for developing ML models that bolster fact-checking efficiency. As a POC, the initial alpha release of Deep Classiflie generates/analyzes a model that continuously classifies a single individual's statements (Donald Trump) using a single ground truth labeling source (The Washington Post). For statements the model d…

A python script for blocking Hindu nationalist trolls on Reddit

Repository for UC Berkeley MIDS Capstone Project (Spring 2023) for team Fake News Bears looking at US politician Twitter data to assess the spread of and exposure to disinformation online.

Social Network Analysis to Help Rescue targeted women/people from abuse, exploitation, harassment, disinformation/influence operations, and threats. Uses webscraping, NLU, cyber intelligence, statistics, botnet detection, clustering, and methods. Female public figure-standard.

A collection of "Memetic Warfare" articles, social media posts, datasets, code implementations, and case studies

A project on designing a deceptive data graphic. Dataset from Toronto's Open Data portal: https://portal0.cf.opendata.inter.sandbox-toronto.ca/dataset/immunization-coverage-for-students/

Deep_classiflie_db is the backend data system for managing Deep Classiflie metadata, analyzing Deep Classiflie intermediate datasets and orchestrating Deep Classiflie model training pipelines. Deep_classiflie_db includes data scraping modules for the initial model data sources. Deep Classiflie depends upon deep_classiflie_db for much of its anal…

Fake news detection using Natural Language Processing

Documentation & Client for API which return bad websites according to nfnz.cz, konspiratori.sk and nelez.cz

Online Disinformation Spreading Through Deepfakes

A community initiative providing knowledge about COVID-19 and vaccines to those who are lost in the disinformation

Top pro-Russian sources in Slovakia

Troglodyte Networked Conspiracy Database

API Services: Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society

Formations, cours particuliers et à domicile sur Montpellier

a consolidated and cleaned up fake news dataset classified in the following categories: reliable, unreliable, political, bias, fake, conspiracy, rumor clickbait, junk science, satire, hate

Code for the Digital Journalism paper: 'Digital Infrastructures of COVID-19 Misinformation: A New Conceptual and Analytical Perspective on Fact-Checking'. In the paper we compare two fact-checking databases (Poynter institute and Google Fact-check explorer) as overarching infrastructures of fact-checking.

R code, markdown document, and Gephi files used to create a social network analysis project examining three information operations removed from Twitter in 2021.