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Project #Marius
Chris Zimmerman
Ravi Vatrapu
Yuran Chen
Dan Hardt
Social Business Intelligence
Real World Reflections
Toolset
Tool

Purpose

Access

Radian6

Collection

License

Nitrogram

Collection

License

Tableau Desktop Visualization / Analysis

License (edu)

Datawrapper

Visualization

Public

TimelineJS

Visualization

Public

LIWC

Language Analysis

Public

SODATO

Collection / Vizualization Beta

Topsy Pro

Collection / Analysis

Trial

Scoailbakers

Facebook Statistics

COTS*

Followerwonk

Context

COTS*

Twtrland

Context

COTS*

Quintly

Context

COTS*

Wildfire

Historical Performance

COTS*

Consumer of the shelf tool (COTS)
#Marius Overview
Social Data Collected
• 40 Online Channels (Jan 19 – Feb 19)
• Over 315 K Posts Collected (75% Twitter)
• 200 K Unique Posts (63%)
• 681 Million Potential Impressions on Twitter
• Highest Buzz Rate : 332 Posts / Minute
Normal Monthly Volume : 300-500 Stories
• 30K Petition Signatures
• 45K Facebook Protesters
Visual Analysis & Full Dataset

(click here)
Research Avenues of Inquiry
The online reflection - Why does this matter?

• Volume – How did the conversation amplitude evolve over
two weeks in February online?
• Sentiment – Where did negative sentiment originate and how
did it evolve/spread? (keywords, people, and topics)
• Community – Who were the relevant actors? (Organizations,
Customers, Users, Activists, Influencers, etc.)
• Post-level Performance – What types of posts and specific
events instigated the issue online? (artifacts involved such as
videos, photos, Facebook posts, tweets, etc)
How did the Copenhagen Zoo handle the event on social
channels and how did the (social) media storm effect their
presence? How did other organizations deal with the crisis?
What made this incident different and how?
Dataset
Distribution
Distribution (DK)
Channel Comparison
•

•

Twitter dominates 75% of total
chatter, while 21% is from Facebook
Discussions
Amplification: 50% of Tweets are
retweets

Danish Subset
• Media channels are more rich in
diversity
• Facebook and Twitter only share
half the conversation
• Only a quarter of all Tweets are retweets
> Does mainstream media play a
greater role for Danish society while,
social media is dominant elsewhere in
terms of quantity of discussion and
breadth of dispersion?
Region and Language
Detection
• 95% of the total
conversation was
detected to be in English.
• Almost two thirds of
global activity came from
the US (64%), followed by
the UK (13%) and
Netherlands (4%).
• Danish was only detected
in 2,220 posts.
Timeline of Events

(click here)
Social Text
A Sentimental Topic
Radian6
Sentiment-challenged Examples:
Automatic Sentiment Results
• Danish data tends to be
much more neutral
compared to the nonDanish data.
• Most of the negativity
detected in Twitter for
non-Danish data while
most of the negative
data occurs in
Facebook for Danish
data.
> Does this imply that
Danes prefer Facebook to
Twitter to express their
ideas?
Language Comparison
#Marius Demographics
Location estimates
North America
usage over 50%
Twitter bio field
reveals several
dominant traits
during the weekend:
•
•
•
•
•
•

Liberal,
Progressivism,
Vegan,
Activist,
Animal rights,
advocate, pets, wil
dlife, etc
Network Analysis
Amplification Influentials

#Marius

@CopenhagenZoo
Amplified Posts
Centrality

Vertex
copenhagenzoo

InOutBetweenness Closeness Eigenvector
Degree Degree Centrality
Centrality Centrality

Clustering
PageRank Coefficient

513

0

767401.779

0.001

0.038

122.346

digitalcake2

1

62

89745.114

0.000

0.004

aprilchristen

27

5

41415.806

0.000

beaumiroir

14

7

39865.026

01bond

38

1

rtenews

37

ebizniz

Custom Menu Item Action

Tweete
d
Search
Term?

0.002https://twitter.com/copenhagenzoo

No

17.351

0.009https://twitter.com/digitalcake2

Yes

0.001

8.279

0.016https://twitter.com/aprilchristen

Yes

0.000

0.001

5.353

0.023https://twitter.com/beaumiroir

Yes

32366.167

0.000

0.000

9.443

0.000https://twitter.com/01bond

Yes

0

28708.167

0.000

0.000

8.838

0.000https://twitter.com/rtenews

No

1

9

23755.440

0.000

0.000

3.216

0.000https://twitter.com/ebizniz

Yes

mmpr_consultant

17

6

19567.043

0.000

0.003

4.570

0.082https://twitter.com/mmpr_consultant

Yes

earthtransition

12

1

19429.063

0.000

0.000

4.656

0.006https://twitter.com/earthtransition

Yes
Copenhagen Zoo Facebook
Performance
• Largest surge in likes ever
• Almost 100K People
Talking About This (PTAT)
on Facebook
• 120.3% Normalized Buzz
(PTAT/Likes)

Global Fan Growth
• Over 10K new fans this
month (70% in Denmark)
• 19 Countries more than
doubled their fanbase
• Countries such as the UK
and Australia tripled and
almost quadrupled their
fanbases of CPH Zoo.

Likes

PTAT

PTAT / Likes
Interactions (LCS Historical)
Check-ins
• Beforehand, 29K
people added the
Zoo’s location to a
Facebook post
• Now 110K people
“Were Here” on
Facebook
• CPH Zoo is thus now
the 7th most checkedinto place in Denmark
Initial Findings
Overall
• Twitter offered a more direct reflection of events, in terms
of volume and sentiment
• Twitter also demonstrated a more drastic reaction to
network prestige factors from activists and celebreties
• Automatic sentiment on Radian6 is neutral-heavy, often
failing to detect negative sentiment,
• The dominance of English-language countries and the
Twitter channel went hand-in-hand (perhaps along with
mainstream spin).
• The mechanisms on Facebook allow a dichotomy from
crisis situations by yielding negative sentiment in terms of
comments and posts, while simultaneously experiencing
unprecedented growth in positive signals (such as fans
and likes, as well as buzz and check-ins).
Danish Comparison
Contrast with Danish Subset
• Mainstream media plays a larger role as
opposed to higher proportions of online
debate on social channels elsewhere
• Re-tweets levels are relatively small and
social media may be used social media
more to express oneself rather than to
share information.
• Negative sentiment was detected more
strongly on Facebook
@socialbeit
@roamingdata
chris@mindjumpers.com
dk.linkedin.com/in/cjzimmerman

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Visualizing the Social Data of #Marius

  • 1. Project #Marius Chris Zimmerman Ravi Vatrapu Yuran Chen Dan Hardt
  • 4. Toolset Tool Purpose Access Radian6 Collection License Nitrogram Collection License Tableau Desktop Visualization / Analysis License (edu) Datawrapper Visualization Public TimelineJS Visualization Public LIWC Language Analysis Public SODATO Collection / Vizualization Beta Topsy Pro Collection / Analysis Trial Scoailbakers Facebook Statistics COTS* Followerwonk Context COTS* Twtrland Context COTS* Quintly Context COTS* Wildfire Historical Performance COTS* Consumer of the shelf tool (COTS)
  • 5. #Marius Overview Social Data Collected • 40 Online Channels (Jan 19 – Feb 19) • Over 315 K Posts Collected (75% Twitter) • 200 K Unique Posts (63%) • 681 Million Potential Impressions on Twitter • Highest Buzz Rate : 332 Posts / Minute Normal Monthly Volume : 300-500 Stories • 30K Petition Signatures • 45K Facebook Protesters
  • 6. Visual Analysis & Full Dataset (click here)
  • 7. Research Avenues of Inquiry The online reflection - Why does this matter? • Volume – How did the conversation amplitude evolve over two weeks in February online? • Sentiment – Where did negative sentiment originate and how did it evolve/spread? (keywords, people, and topics) • Community – Who were the relevant actors? (Organizations, Customers, Users, Activists, Influencers, etc.) • Post-level Performance – What types of posts and specific events instigated the issue online? (artifacts involved such as videos, photos, Facebook posts, tweets, etc) How did the Copenhagen Zoo handle the event on social channels and how did the (social) media storm effect their presence? How did other organizations deal with the crisis? What made this incident different and how?
  • 11. Channel Comparison • • Twitter dominates 75% of total chatter, while 21% is from Facebook Discussions Amplification: 50% of Tweets are retweets Danish Subset • Media channels are more rich in diversity • Facebook and Twitter only share half the conversation • Only a quarter of all Tweets are retweets > Does mainstream media play a greater role for Danish society while, social media is dominant elsewhere in terms of quantity of discussion and breadth of dispersion?
  • 12. Region and Language Detection • 95% of the total conversation was detected to be in English. • Almost two thirds of global activity came from the US (64%), followed by the UK (13%) and Netherlands (4%). • Danish was only detected in 2,220 posts.
  • 17. Automatic Sentiment Results • Danish data tends to be much more neutral compared to the nonDanish data. • Most of the negativity detected in Twitter for non-Danish data while most of the negative data occurs in Facebook for Danish data. > Does this imply that Danes prefer Facebook to Twitter to express their ideas?
  • 19. #Marius Demographics Location estimates North America usage over 50% Twitter bio field reveals several dominant traits during the weekend: • • • • • • Liberal, Progressivism, Vegan, Activist, Animal rights, advocate, pets, wil dlife, etc
  • 23. Centrality Vertex copenhagenzoo InOutBetweenness Closeness Eigenvector Degree Degree Centrality Centrality Centrality Clustering PageRank Coefficient 513 0 767401.779 0.001 0.038 122.346 digitalcake2 1 62 89745.114 0.000 0.004 aprilchristen 27 5 41415.806 0.000 beaumiroir 14 7 39865.026 01bond 38 1 rtenews 37 ebizniz Custom Menu Item Action Tweete d Search Term? 0.002https://twitter.com/copenhagenzoo No 17.351 0.009https://twitter.com/digitalcake2 Yes 0.001 8.279 0.016https://twitter.com/aprilchristen Yes 0.000 0.001 5.353 0.023https://twitter.com/beaumiroir Yes 32366.167 0.000 0.000 9.443 0.000https://twitter.com/01bond Yes 0 28708.167 0.000 0.000 8.838 0.000https://twitter.com/rtenews No 1 9 23755.440 0.000 0.000 3.216 0.000https://twitter.com/ebizniz Yes mmpr_consultant 17 6 19567.043 0.000 0.003 4.570 0.082https://twitter.com/mmpr_consultant Yes earthtransition 12 1 19429.063 0.000 0.000 4.656 0.006https://twitter.com/earthtransition Yes
  • 24. Copenhagen Zoo Facebook Performance • Largest surge in likes ever • Almost 100K People Talking About This (PTAT) on Facebook • 120.3% Normalized Buzz (PTAT/Likes) Global Fan Growth • Over 10K new fans this month (70% in Denmark) • 19 Countries more than doubled their fanbase • Countries such as the UK and Australia tripled and almost quadrupled their fanbases of CPH Zoo. Likes PTAT PTAT / Likes
  • 26. Check-ins • Beforehand, 29K people added the Zoo’s location to a Facebook post • Now 110K people “Were Here” on Facebook • CPH Zoo is thus now the 7th most checkedinto place in Denmark
  • 27. Initial Findings Overall • Twitter offered a more direct reflection of events, in terms of volume and sentiment • Twitter also demonstrated a more drastic reaction to network prestige factors from activists and celebreties • Automatic sentiment on Radian6 is neutral-heavy, often failing to detect negative sentiment, • The dominance of English-language countries and the Twitter channel went hand-in-hand (perhaps along with mainstream spin). • The mechanisms on Facebook allow a dichotomy from crisis situations by yielding negative sentiment in terms of comments and posts, while simultaneously experiencing unprecedented growth in positive signals (such as fans and likes, as well as buzz and check-ins).
  • 28. Danish Comparison Contrast with Danish Subset • Mainstream media plays a larger role as opposed to higher proportions of online debate on social channels elsewhere • Re-tweets levels are relatively small and social media may be used social media more to express oneself rather than to share information. • Negative sentiment was detected more strongly on Facebook

Editor's Notes

  1. Legacy of this Giraffe - Work in progressNext thing – another animal rights incident with a whale has come and gone, twitter has long since moved onNonetheless still tell the story of an explosion on social media with some pretty rich and large data
  2. - For both Danish and non-danish the major media providers are Twitter and Facebook, but the media channel is more diverse for non-danish data, without the predominance of Twitter- Given that retweet take a more important role for non-danish data while Facebook is more popular for Danish, does mainstream media play a greater role for Danish society while in non-danish data, social media is now dominant in terms of quantity of discussion and breadth of dispersion?- It is interesting to see that Retweets for Danish data are proportionally small. Does this imply that Danes use social media more to express themselves rather than to share information?
  3. Sources : Sentiment140, Twtrland
  4. People with large followers also play an essential role in spreading the information. For example @rickygervais ( English comedian) and @fielaursendk( Danish blogger)
  5. Lets talk about Facebook, after the twitter-heaviness of the overall online conversation