Hoaxy: A Platform for Tracking Online Misinformation
arXiv:1603.01511 · doi:10.1145/2872518.2890098
Abstract
Massive amounts of misinformation have been observed to spread in uncontrolled fashion across social media. Examples include rumors, hoaxes, fake news, and conspiracy theories. At the same time, several journalistic organizations devote significant efforts to high-quality fact checking of online claims. The resulting information cascades contain instances of both accurate and inaccurate information, unfold over multiple time scales, and often reach audiences of considerable size. All these factors pose challenges for the study of the social dynamics of online news sharing. Here we introduce Hoaxy, a platform for the collection, detection, and analysis of online misinformation and its related fact-checking efforts. We discuss the design of the platform and present a preliminary analysis of a sample of public tweets containing both fake news and fact checking. We find that, in the aggregate, the sharing of fact-checking content typically lags that of misinformation by 10--20 hours. Moreover, fake news are dominated by very active users, while fact checking is a more grass-roots activity. With the increasing risks connected to massive online misinformation, social news observatories have the potential to help researchers, journalists, and the general public understand the dynamics of real and fake news sharing.
arXiv comment6 pages, 6 figures, submitted to Third Workshop on Social News On the Web
References in corpus (6)
- Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams
- Computational fact checking from knowledge networks
- The DARPA Twitter Bot Challenge
- Modeling Rumors: The No Plane Pentagon French Hoax Case
- The production of information in the attention economy
- Viral Misinformation: The Role of Homophily and Polarization
Cited by in corpus (59)
- A Survey of Fake News: Fundamental Theories, Detection Methods, and Opportunities
- Influence of fake news in Twitter during the 2016 US presidential election
- Detection and Resolution of Rumours in Social Media: A Survey
- Fake News Detection on Social Media: A Data Mining Perspective
- Anatomy of an online misinformation network
- FakeNewsNet: A Data Repository with News Content, Social Context and Spatialtemporal Information for Studying Fake News on Social Media
- CoAID: COVID-19 Healthcare Misinformation Dataset
- False Information on Web and Social Media: A Survey
- Cashtag piggybacking: uncovering spam and bot activity in stock microblogs on Twitter
- Investigating Italian disinformation spreading on Twitter in the context of 2019 European elections
- Quantifying Biases in Online Information Exposure
- Defending Against Neural Fake News
- Topology comparison of Twitter diffusion networks effectively reveals misleading information
- The Web of False Information: Rumors, Fake News, Hoaxes, Clickbait, and Various Other Shenanigans
- Combating Misinformation in Bangladesh: Roles and Responsibilities as Perceived by Journalists, Fact-checkers, and Users
- The State of Human-centered NLP Technology for Fact-checking
- Automatically applying a credibility appraisal tool to track vaccination-related communications shared on social media
- Modeling the spread of fake news on Twitter
- On the statistical properties of viral misinformation in online social media
- Online Social Deception and Its Countermeasures for Trustworthy Cyberspace: A Survey
- Research Status of Deep Learning Methods for Rumor Detection
- The Rise of Guardians: Fact-checking URL Recommendation to Combat Fake News
- Bot Electioneering Volume: Visualizing Social Bot Activity During Elections
- A Comparative Evaluation of Interventions Against Misinformation: Augmenting the WHO Checklist
- SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours
- Fake Cures: User-centric Modeling of Health Misinformation in Social Media
- False News On Social Media: A Data-Driven Survey
- Human-centered NLP Fact-checking: Co-Designing with Fact-checkers using Matchmaking for AI
- Dataset of Fake News Detection and Fact Verification: A Survey
- #ArsonEmergency and Australia's "Black Summer": Polarisation and misinformation on social media
- SciLens: Evaluating the Quality of Scientific News Articles Using Social Media and Scientific Literature Indicators
- Technology-Enabled Disinformation: Summary, Lessons, and Recommendations
- RumourEval 2019: Determining Rumour Veracity and Support for Rumours
- Human-Misinformation interaction: Understanding the interdisciplinary approach needed to computationally combat false information
- CoSINT: Designing a Collaborative Capture the Flag Competition to Investigate Misinformation
- SciClops: Detecting and Contextualizing Scientific Claims for Assisting Manual Fact-Checking
- Using Deep Networks and Transfer Learning to Address Disinformation
- Dissecting the Meme Magic: Understanding Indicators of Virality in Image Memes
- Bootstrapping Domain-Specific Content Discovery on the Web
- Vulnerable to Misinformation? Verifi!
- Reputation Systems for News on Twitter: A Large-Scale Study
- Learning from Fact-checkers: Analysis and Generation of Fact-checking Language
- OSINT Research Studios: A Flexible Crowdsourcing Framework to Scale Up Open Source Intelligence Investigations
- Stance Prediction for Russian: Data and Analysis
- Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content
- A multi-layer approach to disinformation detection on Twitter
- How does Truth Evolve into Fake News? An Empirical Study of Fake News Evolution
- SOK: Fake News Outbreak 2021: Can We Stop the Viral Spread?
- Combating fake news by empowering fact-checked news spread via topology-based interventions
- WhatTheWikiFact: Fact-Checking Claims Against Wikipedia
- The Phase Model of Misinformation Interventions
- A Classification Algorithm to Recognize Fake News Websites
- Beyond Trolling: Malware-Induced Misperception Attacks on Polarized Facebook Discourse
- Towards the Modeling of Behavioral Trajectories of Users in Online Social Media
- Identifying Fake News from Twitter Sharing Data: A Large-Scale Study
- Towards Understanding the Information Ecosystem Through the Lens of Multiple Web Communities
- Universal Fake News Collection System using Debunking Tweets
- REMOD: Relation Extraction for Modeling Online Discourse
- Mining Social Media for Newsgathering: A Review