This is super interesting research!
- Build a tool that helps streamline the process of sending corrections (and essential updates) down the media pathways the original stories traveled. The tool will include research-oriented features that encourage experimentation, such as A/B testing to see what language gets the best results. We’ll be open-sourcing this work along the way.
I’m reminded of Sandy Pentland’s social physics research out of MIT. Y’all might remember them as the team that (with only a few weeks planning) orchestrated the winning strategy in DARPA’s grand challenge for finding 10 random balloon scattered in USA in shortest amount of time.
I wonder if a neat strategy might be to recruit readers into correction network as the “cost” of accessing the article. So all readers might be recruited into a network of “correction amplifier”, perhaps conceived as a sort of immune response to which a social responsibility to participate is attached. It could be a little like a thunderclap, in that our social media accounts might be authorised to be used on behalf of propagating corrections.
I could imagine that a news agency might have a transparent internal protocol to determine what proportion of the reader network should be used to amplify a correction. So for example, a report with only small impact (but maybe millions of readers) might only have 0.1% of reader Twitter accounts be used to propagate a minor correction. But a big story with tons of readers and high severity correction might deploy 10% of network.
And perhaps syndicating stories might come with expectations of organisations social media accounts. (e.g., BoingBoing syndicating an article would be expected to authorise its own social media accounts into the system.)
Curious if folks have thoughts on this scheme 
What are its weaknesses? What are ways to improve it? Do you think its feasible – technically or politically or whatever?
