Open Source
Github repositories for OSoMe software
We conduct a preregistered experiment to investigate whether fact checks provided by a large language model can serve as an effective misinformation intervention.
This repo contains the code and information for the paper "Anatomy of an AI-powered malicious social botnet"
This repository contains the code for the paper "Exposure to social bots amplifies perceptual biases and regulation propensity."
A Python API for Botometer by OSoMe
This repository contains the code for the paper "Botometer 101: Social bot practicum for computational social scientists."
BotSlayer Community Edition
Code and data for paper "Large language models can rate news outlet credibility"
Python library to detect coordinated campaigns on social media
Reproducibility code for "Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal"
This repo contains the code and information for the paper "Account credibility inference based on news-sharing networks"
Source code and data for paper "Neutral Bots Probe Political Bias on Social Media" by Chen et al.
Echo Chamber Model
Characteristics and prevalence of fake social media profiles with AI-generated faces
friction, social bots, information diffusion
Repository for code & data associated with our paper, A General Language for Modeling Social Media Account Behavior
A web-based framework to visualize dynamic networks in real-time.
Backend component for Hoaxy, a tool to visualize the spread of claims and fact checking
Frontend component for Hoaxy, a tool to visualize the spread of claims and fact checking
Code and instructions to reproduce the results in the paper "The spread of low-credibility content by social bots" by Shao et al.
Code for the replication of results contained in "Political audience diversity and news reliability in algorithmic ranking" by Bhadani et al.
Computational Fact Checking from Knowledge Networks
Code to reproduce results in "Finding Streams in Knowledge Graphs to Support Fact Checking"
Develop and test a simple metric (FIB index) for predicting superspreaders of misinformation on social media.
Code for replicating "Right and left, partisanship predicts vulnerability to misinformation" by Dimitar Nikolov, Alessandro Flammini and Filippo Menczer
OSoMe API mashups
This dashboard enables users to efficiently conduct query searches across different Mastodon instances, facilitating data collection and analysis.
Grab the data from N mastodon streams and provide a central mastodon streamer with a simple token based authentication.
OSoMe Twitter tools. Including a package like tweepy but for the v2 Twitter api.
A Python package that can be used to calculate misinformation-exposure scores for a user based on the falsity scores of public figures they follow on Twitter.
Rematch: Robust and Efficient Matching of Local Knowledge Graphs for Improved Structural and Semantic Similarity
A minimal model of information-sharing on a social media platform.
The Top FIBers dashboard tracks and reports on the top ten superspreaders of low-credibility information on Twitter and Facebook each month, using the FIB-index.
This repository contains the code and data for the paper "The Manufacture of Partisan Echo Chambers by Follow Train Abuse on Twitter."
Code for reproducing the data filtering and analyses in our paper Measuring Online Social Bubbles