Rumor validating

The authors note that “true rumors are more viral — in the sense that they result in larger cascades — achieving on average 163 shares per upload whereas false rumors only have an average of 108 shares per upload.” Even when people discover the falsity of a rumor and delete their reshare, it does not appear to affect the unfolding cascade.The “popularity of rumors — even ones that have been circulating for years in various media such as email and online social networks — tends to be highly bursty.Released under the Creative Commons license, it provides tools, techniques and step-by-step guidelines for how to deal with user-generated content during emergencies.review: “Verification Handbook Mixes Tools, Tips and Culture for Fact-Checking.”The Verification Handbook for Investigative Reporting: A follow-up to , this guide highlights techniques for leveraging user-generated content and open-source information in investigative reporting.

K.-based site covers information on the economy, health, crime and the law, immigration and education.

The paper provides interesting data about the way fake images spread during Sandy, and explores how one day we may be able to flag tweets as potentially containing false information.

article: “New Research Suggests It’s Possible to Automatically Identify Fake Images on Twitter.”Dynamic Network Analysis: On Jan.

Checkdesk: A verification tool designed to help curate user-generated content during breaking news and connect journalists to citizen sources on the ground.

“Checkdesk facilitates collaborative fact-checking of unverified reports,” the developers write.

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