Measuring the Impact of CIR's Veterans Reporting
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Transcript of Measuring the Impact of CIR's Veterans Reporting
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Amy Pyle, Senior Editor Aaron Glantz, Reporter
Cole Goins, Distribution & Engagement Mgr. Lindsay Green-Barber, Ph.D.,
Media Impact Analyst, ACLS Public Fellow #DissectionD
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Story 1: The VA backlog
#DissectionD
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Response ● Iraq and Afghanistan Veterans
of America issues news release
● Newspaper Editorials (NY Times, LA Times)
● The Daily Show picks up cause, cites CIR in “Red Tape Diaries”
● VA Secretary Shinseki gives first interview in four years
#DissectionD
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Congress intervenes
● 67 Senators write to Obama ● 160 members of the House of
Representatives write to Obama
#DissectionD
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Data App 1: Backlog • Backlog API came
out two months after story broke
• Required a lot of
hand-to-hand outreach
• Only track visits
#DissectionD
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Text analysis
Data set: Presidential speeches that include the words “veteran” and “backlog”
22 total, 17 relevant
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Findings 2009
3 instances 1 military Funding Tech
2010
7 instances 2 military Progress Funding Tech
2011
1 instance 1 military Increase Funding Tech
2012
2 instances 2 military Funding Tech Attack
2013
2 instances 2 military Attack Progress
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Obama responds
#DissectionD
Five months after our story ran: “Finally the backlog is shrinking. In the last five months alone, it’s down nearly 20%.” - August 2013
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Story 2: Backlog drops
#DissectionD
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Story 3: Opiates
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Data app 2: Opiates • “How to” guide
published with API • Analytics at level of
event • Localized stories for
regions with highest prescription levels
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Localized coverage by CIR
#DissectionD
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ABC News partnership
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Response • Two congressional hearings • New non-narcotic pain
therapies being rolled out across the country
• 20,000 fewer veterans on
opiates #DissectionD
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Challenges in Impact Analysis • Lack of standards
• Question of engagement
• Overabundance of online analytics
• Offline activity
#DissectionD
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Phase 1: Needs Assessment • Definition of Impact
• Conceptualization of Impact
• Method for tracking Impact
• Method for comparing across stories and platforms
• Community building #DissectionD
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Impact = change in the status quo as a result of a direct intervention, be it a text article, live
event, or radio or TV program.
Conceptualization
Macro
Meso
Micro
#DissectionD
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Reach
Impact
After the story breaks
#DissectionD
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Internal communication
• Weekly newsletter
• Blog posts
• Outcome Reports
#DissectionD
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Next steps • Data
• Testing & analysis
• Communications
• Community of practice
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Impact assessment methodology • Identify outcomes
Macro - government response, change in policy Meso - increased conversation around issues Micro - increased awareness
• Identify processes Text analysis (human and automated)
#DissectionD
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Targeted distribution + Organic pickup
#DissectionD
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Data apps traffic • Bumps not when stories published,
especially for Backlog • Reveal Radio single largest driver of traffic
to any data app on CIR’s site • Alabama Media Group’s share of the app
(al.com) resulted in a wave of traffic
#DissectionD
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Text analysis (Wordseer)
#DissectionD
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Takeaways • Partnerships can help a story be localized
meaningfully • Reach is more than distribution through
media • Public discourse around an issue can be
measured • Impact is a (long) process
#DissectionD
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Questions?
Aaron Glantz: [email protected] Lindsay Green-Barber: [email protected] Cole Goins: [email protected] Amy Pyle: [email protected]
#DissectionD