Breaking News

A "News" story that is new/reactive enough to be constantly changing with new information.

Wikipedia is often surprisingly good for this.

Design of a Hypertext Breaking News Medium

Jan'2015

• Watching the recent "NewsRoom" season premiere dealing with handling the Boston Marathon bombing made me think about this. Then re-discovered what I wrote at the time: 2013-04-15-BostonMarathonBombings
• A related bit I wrote since then: 2013-09-08-AssembleItYourselfComponentBasedJournalism
• This week's Charlie Hebdo bombing, esp this Jay Rosen tweet, reinforced my thinking...
• A mental conflict: to some extent I think even a good solution here doesn't serve humanity because in reality most Breaking News is Meaningless for most people.

Context/goals

• When people hear about a "big event", they want to know the details right away (Real Time).

Forces

• A traditional "story" weaves a Narrative around a collection of facts
• There are many small claims (pieces of information) coming from many sources
• Many of those claims can't be immediately verified.
• Readers/viewers keep arriving and returning at any time

Solution

• The unit of information is the Claim - a small objective statement describing a bit of reality.
• Each claim should be written in EPrime, and as narrow in scope as possible.
• Claims can be submitted by staff or 3rd parties (Crowd Sourcing)
• Documents can also be submitted. These might be interviews performed by staff, articles/tweets/posts from the web, etc.
• Every document should be associated with 1 or more Claims.
• A Claim has a created-timestamp, a document has a created-timestamp, and a link (between a Document and a Claim) has a created-timestamp.
• Documents from 3rd parties should be scraped/stored. Then periodically re-scraped and compared. Changes in documents should be shown.
• Allow anyone to "rate" every Claim in terms of % certainty they hold it. Eyewitness=100%, complete counter-proof=0%
• Allow staff to "rate" every Claim, in a way that over-rides crowd rating.
• For staff ratings, it probably makes sense to have 3-5 buckets of certainty. If a Claim is created by the crowd, and thus initially un-rated by staff, it should start out in the middle-bucket of staff-rating representing Uncertainty.
• Then you can list Claims in order of staff-rating, then ordered by crowd-rating within each bucket.
• Staff and Crowd can also equivalently flag Documents for credibility and other value (being well-written, etc.)
• Staff can also flag Document-links as strongly driving the staff-rating of a Claim.
• App should track changes in crowd-rating in time to trigger some sort of staff review.
• It should be possible to write new/improved Claims similar to already-existing Claims, then flag the old Claims as obsolete with a link to the current claim. Maybe only staff can do this.
• Staff can have some way of clustering related Claims, and giving a name/subhead for that bucket. This will drive the initial view of a visitor.
• A returning visitor will get a default view highlighting Claims that have been added or significantly changed in rating since their last visit.
• When viewing a Claim the reader will see the collection of linked Documents, sorted by rating.
• what else?

Jan11'2015 update

• I'm not sure whether a "story" looks like an Outline of claim-clusters, or more of a Mind Map or some other visual thing.
• My inspirations for claim granularity/writing:
  • Structured Writing
  • Idea Futures
  • Earth Web Book, Brins Earth
  • Jeff Jarvis: Now let’s deconstruct the article into its core assets. Let’s unbundle its elements just as news publications themselves have been unbundled. Draw that inverted pyramid and its constituent elements and then imagine each as a separate entity in its optimal form.
• Jay Rosen thinks the unit of information should be the Verifiable Claim: something that can be verified. I think you want to make Verified claims more prominent, but part of the goal is to surface crowd-rated claims to drive verification-attention, and to address them before they are verified: "lots of people are saying this, but we've only found this marginal support for it so far".
• Jay Rosen points at Craig Silverman's Emergent Info site.
  • Very cool.
  • Claims are bucketed as True/False/Unverified. That reminds me of Robert Anton Wilson's categorizing truth-level (Nature Of Truth), but not in an actionable way...
  • Some Claims are flagged as Controversial.
  • In his model, the Claim is the Story. I think that esp in Breaking News there are lots of Claims around a single Event's Story that need their own attention.
    • Further, I think it would be interesting to later extend a similar model to lots more Journalism - break a story up into specific Claims. I think this might move us forward toward a Disputation Arena model, with less partisan talking-past-each-other.
  • Every Document is bucketed as For/Against/Observing the Claim.
    • the Sharing volume of each Document is tracked, and summed up to give an overall Sharing level of the Claim. So then there's a Most-Shared list of Claims - amusingly most are False.
  • Claims(/Stories) are Tagged, which kinda does the same thing as Clustering, but that's more about clustering Stories over time, rather than narrow Claims currently under investigation.
  • Here's a key post and their blog about their process/thinking.
  • Note that there's no user/"citizen" involvement here, other than being able to email them.
  • Update/update: Craig Silverman notes they've got plans for more features...
  • Apr'2015: and, it's dead. Ironically, Silverman moved to BuzzFeed.

What changes to above are needed for clusters of HyperLocal info?

Example: 2012-12-03-JournalismServiceListsOutlinesAndData