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The Newsroom of Things
ISKO UK “Taming the News Beast”
April 2014
matt shearer – innovatio...
ABOUT US
“Driving Innovation in News”
NEW TECH AND
DATA
OPPORTUNITIES
NEW
JOURNALISM
FORMATS
EXPLORE
VIA
PROTOTYPING
Part ...
WHAT ARE WE* DOING?
* BBC NEWS
Focussing on the next 8 yrs.
INFORM
EDUCATE
ENTERTAIN
DIFFERENTIATOR?
Storytelling with
BBC (+) content
past & present
GLOBAL
CURATION
HOW?
GLOBAL
CURATION
MACHINES DO
HEAVY LIFTING:
Discovery
JOURNALISTS:
Amazing Creative Efficiency.
100% time on curation.
0% t...
“Stuff & Things”
(and stuff)
The Newsroom of THINGS
30 Languages.
+ 24/7
+ Global
+ Radio + Online + TV
= a lot of things
HOW DO WE GET
THE THINGS?
THE MACHINES
DISCOVER
THE THINGS
It’s notNEW
ROCKET SCIENCE
TEXT
…well explored
Things in
is a bit more exciting
AV …Things in
Stuff & Things (all 6 types = holy grail)
1.Verbatim transcript (to time) “…where she says „damnit!‟”
2.Contributors (face...
from combinations of
this stuff & things
relevance
Then we get real
this stuff & things
connecting
and from
Since 2012:
R&D JUICER
What is it?
• News Content
• Tagged with Linked Data concepts
1
Get
Content
2
Extract
Concepts
3
Match to
DBpedia
4
Annota...
“THINGS”
AT PRESENT:
Topics: PEOPLE, PLACES, ORGANISATIONS
& themes.
NEAR FUTURE:
Storylines: curated “Story” – an editori...
What’s the content?
Unique Things
…used how many times?
Summary figures
• 680,000 articles tagged with 5,700,000 tags
• ~8 tags per article
We save a lot of manual tag time
tags in Juicer 5,700,000
seconds per tag guestimate 10
total seconds on tagging 57,000,00...
Next :
Window on the Newsroom
(+AV with transcript generation and speaker recognition)
and after that:
GLOBAL
JUICER
spaces we are in:
Journalism as Data
MetaJournalism
Object-based Broadcast
Come explore with us!
See: newsHACK.co.uk
1st & 2nd May.
#newsHACK II. Glasgow & Dublin
(News Orgs and Academics)
@BBC_News_Labs
Thanks
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The Newsroom of Things by BBC News Labs - for ISKOUK "Taming the News Beast"

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This presentation outlines how BBC News Labs is currently working on entity extraction on BBC News content.

It looks at the challenge of how BBC News is going to leverage it's USP of Storytelling, and it's famous purpose - "to INFORM, EDUCATE & ENTERTAIN" globally.
With the millions and millions of "things" that are in our content, how do we discover and connect these things?..

It also mentions 2 key BBC News Labs projects "JUICER" and "#newsVANE", and promotes the http://newshack.co.uk/newshack-ii/ event on May 1st in Dublin & Glasgow.

Veröffentlicht in: Daten & Analysen
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The Newsroom of Things by BBC News Labs - for ISKOUK "Taming the News Beast"

  1. 1. Powered by BBC Connected Studio The Newsroom of Things ISKO UK “Taming the News Beast” April 2014 matt shearer – innovation manager @BBC_News_Labs
  2. 2. ABOUT US “Driving Innovation in News” NEW TECH AND DATA OPPORTUNITIES NEW JOURNALISM FORMATS EXPLORE VIA PROTOTYPING Part of BBC Connected Studio. The BBC‟s open innovation programme.
  3. 3. WHAT ARE WE* DOING? * BBC NEWS
  4. 4. Focussing on the next 8 yrs.
  5. 5. INFORM EDUCATE ENTERTAIN
  6. 6. DIFFERENTIATOR?
  7. 7. Storytelling with BBC (+) content past & present GLOBAL CURATION
  8. 8. HOW?
  9. 9. GLOBAL CURATION MACHINES DO HEAVY LIFTING: Discovery JOURNALISTS: Amazing Creative Efficiency. 100% time on curation. 0% time on digging and filing… MORE MACHINE WORK: Connecting and Surfacing “juicer” “#newsVANE” Stuff & Things Trends & Signals
  10. 10. “Stuff & Things” (and stuff) The Newsroom of THINGS
  11. 11. 30 Languages. + 24/7 + Global + Radio + Online + TV = a lot of things
  12. 12. HOW DO WE GET THE THINGS?
  13. 13. THE MACHINES DISCOVER THE THINGS
  14. 14. It’s notNEW ROCKET SCIENCE
  15. 15. TEXT …well explored Things in
  16. 16. is a bit more exciting AV …Things in
  17. 17. Stuff & Things (all 6 types = holy grail) 1.Verbatim transcript (to time) “…where she says „damnit!‟” 2.Contributors (face and voice) “who‟s in this segment?” 3.Objects (audio & image recog) “tank or a elephant?” 4.Scene geolocation “this looks like Bangor” 5.Topics mentioned (people, places, orgs,.. Storylines*) 6.Actions & Events (non verbal) “people laughing, kissing” * Jeremy is telling you in a few mins…
  18. 18. from combinations of this stuff & things relevance Then we get real
  19. 19. this stuff & things connecting and from
  20. 20. Since 2012: R&D JUICER
  21. 21. What is it? • News Content • Tagged with Linked Data concepts 1 Get Content 2 Extract Concepts 3 Match to DBpedia 4 Annotate Content 5 Push to Triplestore The Juicer 6 Expose via API
  22. 22. “THINGS” AT PRESENT: Topics: PEOPLE, PLACES, ORGANISATIONS & themes. NEAR FUTURE: Storylines: curated “Story” – an editorial THING
  23. 23. What’s the content?
  24. 24. Unique Things
  25. 25. …used how many times?
  26. 26. Summary figures • 680,000 articles tagged with 5,700,000 tags • ~8 tags per article
  27. 27. We save a lot of manual tag time tags in Juicer 5,700,000 seconds per tag guestimate 10 total seconds on tagging 57,000,000 Mins spent 950,000 Hours 15,833 working days tagging 1,979 working years tagging 9 NB – this is rough, and just for illustration.
  28. 28. Next : Window on the Newsroom (+AV with transcript generation and speaker recognition)
  29. 29. and after that: GLOBAL JUICER
  30. 30. spaces we are in: Journalism as Data MetaJournalism Object-based Broadcast
  31. 31. Come explore with us! See: newsHACK.co.uk 1st & 2nd May. #newsHACK II. Glasgow & Dublin (News Orgs and Academics)
  32. 32. @BBC_News_Labs Thanks Powered by BBC Connected Studio

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