Social media hoaxes: Could machine learning debunk false Twitter rumors before they spread?
By Will Oremus, Slate Magazine, Dec 14, 2002
When something momentous is unfolding—the Arab Spring, Hurricane Sandy, Friday’s horrific elementary school shooting in Connecticut—Twitter is the world’s fastest, most comprehensive, and least reliable source of breaking news. If you were on the microblogging site Friday afternoon, you were among the first to hear the death toll, watch the devastated reactions, and delve into the personal details of the man the media initially identified as a killer. But there’s also a good chance you were taken in by some of the many falsehoods that were flying, like a letter one of the young victims purportedly wrote to his mother before the shooter entered the classroom. And, of course, all of those social media pages that were making the rounds turned out to belong to innocent people, including the real suspect’s brother.
For full text of the article, visit Social media hoaxes: Could machine learning debunk false Twitter rumors before they spread? – Slate Magazine.
- Building a Better Truth Machine (slate.com)
- Predicting the Credibility of Disaster Tweets Automatically (irevolution.net)
- Social Media In a Disaster: From Hoaxes to Healing (blogs.sap.com)
Lea Shanley is the Founder and former Director of the Commons Lab of the Woodrow Wilson International Center for Scholars. She is currently serving as a Presidential Innovation Fellow at NASA and GSA's 18F innovation team on crowdsourcing and citizen science.
Disclaimer: This is a personal blog of links to relevant news, events, and reports, provided for educational purposes only. The opinions and views contained therein are those only of the authors of the original articles. These opinions do not necessarily reflect those of the editor of this blog or or associated organizations.
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