acm-header
Sign In

Communications of the ACM

ACM TechNews

Slowing the Spread of Viral Misinformation: Can Crowdsourcing Help?


View as: Print Mobile App Share:
Running a "truth-o-meter" over suspicious news.

Two University of Washington professors speculate as to what social media platforms should be doing to address the problem of virally spreading misinformation.

Credit: The Huffington Post

Social media platforms play a pivotal role in the modern information-sharing environment's facility with virally spreading misinformation, which leads to speculation as to what actions such platforms can and should take to address the problem, write University of Washington (UW) professors Kate Starbird and Emma Spiro.

They led a comprehensive study of online rumoring during crisis events to better understand how rumors spread and how to devise techniques for automatically detecting rumors in Twitter.

Starbird and Spiro believe their work with crowdsourcing dovetails with the challenge of identifying and curtailing online misinformation. They note their research into "self-correcting" crowdsourcing of rumor posts demonstrated limitations, but suggest expressed uncertainty in message content could help in automatic early detection.

Starbird and Spiro also note the potential of explicit recommendation systems and formal crowdsourcing initiatives, but they say "the most successful solutions are likely to be hybrid ones that integrate automated, [machine-learning] algorithms based on a variety of features with real-time feedback from people to catch errors and refine the models."

However, Starbird and Spiro acknowledge making these methods publicly transparent creates the likelihood of malefactors "gaming" the techniques to avoid identification. They suggest redesigning social media platforms to help people better rate information credibility on their own.

From The Huffington Post
View Full Article

 

Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA


 

No entries found

Sign In for Full Access
» Forgot Password? » Create an ACM Web Account