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© 2017 Proprietary and confidential.

SEPTEMBER 2015

MONITORING VOLKSWAGEN’SEMISSIONS SCANDAL

P O W E R E D B Y

SEPTEMBER 2015

Monitoring Volkswagen’s Emissions ScandalMEDIA CR IS IS ANALYS IS

US news articles about VW from 10 Sep 2015 to 28 Sep 2015

n=2,688 unique articles

FACILITIES

PROCESS

N E W S O V E R T H E P A S T 2 W E E K S B R E A K S D O W N I N T O N E W S A B O U T T H E E M I S S I O N S S C A N D A L A N D N E W M O D E L S / T E C H

Topics Size

Emissionsscandal 85%

Newmodels&tech 15%

D I ES E L , E F F I C I ENCY , & S CANDAL 10%

CONSUMER & CORPORATE IMPL I CAT ION

10%

L AWSU I T S BEG IN 8%

EU REGULAT IONS / S PECULAT IONS

8%

VW S TOCK 7%

HOWVW GOT CAUGHT 7%

US ORDERS RECAL L 6%

WINTERKORN RES IGNS 7%

APOLOGY FOR ‘ BROKEN TRUST ’ 5%

L EADERSH I P S P ECULAT ION 5%

VW ADM ITS ‘ TOTAL L Y S CREWED UP ’ 4%

EXECS SUSPENDED 4%

MUEL L ER I S NEW CEO 4%

VW PUSHES INTO EV S 4%

NEW CAR REV I EWS 4%

S TOCK MARKET RECAPS 3%

2017 T IGUAN 3%

SCANDAL IN CONTEXT OF VW H I S TORY 2%

2016 PAS SAT 2%

US news articles about VW from 10 Sep 2015 to 28 Sep 2015

n=2,688 unique articles

But coverage about the scandal breaks down into many distinct conversations

B Y M O N D A Y 9 / 2 8 , T H E U S N E W S V O L U M E A B O U T V W H A D C O M E B A C K D O W N T O T H E L E V E L O F F R I D A Y 9 / 2 8 , W H E N T H E S T O R Y B R O K E

US ORDERS RECALL

APOLOGY FOR BROKEN TRUST

WINTERKORN RESIGNS

MUELLER IS NEW CEO

Timeline of unique US news articles from 10 Sep 2015 to 28 Sep 2015, colored by topic n=2,688 unique articles

B U T T H E S E N T I M E N T A B O U T V W H A D B E C O M E M U C H M O R E N E G A T I V E …

Timeline of unique US news articles form 10 Sep 2015 to 28 Sep 2015, colored by sentiment

n = 2,688 unique articles.

Sentiment Share

Positive 20%

Neutral 44%

Negative 36%

Sentiment Share

Positive 10%

Neutral 31%

Negative 59%

P R E S S I N T E R E S T B Y S O C I A L R E S O N A N C E

According to broadcast strength and social resonance, articles about consumer and corporate implications are the most popular.

Plot of press interest (publish count) by social resonance (social sharing) of US news articles about VW from 10 Sep 2015 to 28 Sep 2015, colored and grouped by topic.

n=2,688 unique articles

Apology for ‘broken trust’Winterkorn resigns

Consumer & corporate implications(highest social resonance, medium publishing volume)

US orders recall

Lawsuits begin (high publishing volume,medium social resonance)

S E N T I M E N T I N P R E S S

On Monday 9/28, the bulk of well shared articles were negative, but Sir Richard Branson shared some optimism.

Plot of press interest (publish count) by social resonance (social sharing) of US news articles about VW on 28 Sep 2015, colored by sentiment.

n=122 of 2,688 unique articles

“Branson: VW cheating may be positive”CNBC “Qatar fund stands to lose

$5.9 billion on VW, Glendore stakes”Bloomberg

“Former VW head investigated for fraud”CNBC

“European shares weighed down by Glencore and Volkswagen”TheStreet.com

S E N T I M E N T I N T H E P R E S S

On Monday 9/28, Reuters and the financial press published the most articles in the US about VW.

Rank of top 10 US sources publishing about VW by number of unique stories published on 28 Sep 2015, colored by sentiment

n=35 of 2,688 unique articles

S E N T I M E N T I N T H E P R E S S

Of those, Bloomberg, CNBC, and Business Insider had the most social sharing, but auto publications were also influential.

Rank of top 10 US sources publishing about VW by social sharing published on 28 Sep 2015, colored by sentiment

n=35 of 2,688 unique articles

APPENDIX

Similar nodes cluster together, and clusters are grouped by color. Each node represents a document.

Connections represent similar language used

across nodes

A bridging node between two clusters indicates the document is at an

intersection between two concepts.

Peripheral clusters could represent niche takes on the topic

Centrally located nodes are core concepts in the network and share language with many other nodes

Greater distance between clusters indicates a low number of inter-related documents

The density of a cluster indicates how similar or diverse the

nodes are within it

HOW TO READ A NETWORK

TEXT ANALYTICS BACKGROUND

Quid reads any text to identify key words, phrases,

people, companies and institutions.

Then Quid compares words from each document to

create links between them based on similar language.

Quid repeats the process at immense scale, producing a

network that shows how similar all the documents

are to one another.

© 2017 Proprietary and confidential.

P O W E R E D B Y

Quid is software that reads millions of documents and offers immediate insight by organizing that content visually. We power human intuition with machine intelligence, enabling organizations to make decisions that matter.

FOR MORE INFORMATION VIS IT QUID .COM OR

CONTACT US AT H I@QUID.COM

FOLLOW US ON SOCIAL @QUID

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