social network analysis of political change -- from elections to revolutions
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Social Media and the
Revolution in EgyptMaksim Tsvetovat
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Collaboration
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A good psychological warfare executive is no different from amarket research executive, except that the PSYOP officer also
likes to jump out of planes.
Colonel Layton Dunbar, Commander
4th Psychological Operations Group
Operation Desert Storm
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Internet more
ubiquitous thenelectricity
87% of world population are within reachof a cell phone tower (and GPRS/3Ginternet)
80% of world population have some formof electricity accessible
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Ubiquitous Social
Media Twitter has very low barriers to entry
Fast information propagation Fluid communities Largely decentralized
Works on every device including old cellphones (via SMS)
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Freewheeling Media
No established channels or pages #hashtagsused to organize information
-- but are voluntary and freeform
RT @attag:retweet -- spreadsmessages while keeping attribution
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Information
Cascades
Information can cascade throughretweets, and grow exponentially
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Some Statistics
Number of followers on Twitter ispower-law distributed Size of information cascades is power-
law distributed (most go nowhere)
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Result....
A social media outlet that is accessibleand completely uncontrollable byauthorities.
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...only a matter oftime...
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Moldova, 2009
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First Twitter
Revolution... Protests organized using #pmanhashtag Leaderless, real-time, free-form Up to 10,000 people on the streets of
Cisenau
100,000s participating online Results in resignation of president and
parliament and new elections
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Lesson learned...
Being in the right place, in the right time,and somewhat well-connected beatscareful planning
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We were in the rightplace, in the right
time
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Captured Data
Analyzed 25,000,000 relevant tweets over one week Identified communities, sub-communities and mass
influencers related to events in Egypt
Analyzed who actively influenced discussionscausing messages to cascade or go viralCorrelated activity to events in the physical (offline)
world
Highlighted profiles of mass influencers whodemonstrated that when they spoke, other peoplereacted.
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Going Viral Influence in ActionThe larger the node, the greater the reaction to messages
These people influenced action they spoke, people acted
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UNCLASSIFIED
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Mubarak
ResignsMubarqk speech
doesnt resign
EventsTracked reaction online to events as they happened in the real worldCorrelated VOLUME TIME OF DAY / WEEK / MONTH
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UNCLASSIFIED
Daily Cycle
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Online Activity vs World
Events
Correlated VOLUME SPECIFIC EVENTS
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Justin Bieber
Twitter Followers: 7.4 Million
Reactions Generated: 294
Reactions per 1K followers: 0.04
Most Influential vs Most Followed
Wael GhonimTwitter Followers: 86,000+
Reactions Generated: 3,291
Reactions per 1K followers: 38
MASS INFLUENCER
@Weddady Mass Influencer
Twitter Followers: 6,900+
Reactions Generated: 1,281
Reactions per 1K followers: 186
1
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dd dUNCLASSIFIED
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weddadyTwitter Followers: 5,500
Reactions Generated: 1,808
Reactions per 1K followers: 186
1
UNCLASSIFIED
UNCLASSIFIED
UNCLASSIFIED
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DimaKhatib
Twitter Followers: 17,396
Reactions Generated: 1,694
Reactions per 1K followers: 97
2
UNCLASSIFIED
UNCLASSIFIED
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Deena
Twitter Followers: 888
Reactions Generated: 108
Reactions per 1K followers: 122
21UNCLASSIFIED
UNCLASSIFIED
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@5orm
Twitter Followers: 1,938
Reactions Generated: 256Reactions per 1K followers: 132
2UNCLASSIFIED
UNCLASSIFIED
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SaloumehZ
Twitter Followers: 2,692
Reactions Generated: 990Reactions per 1K followers: 334
2UNCLASSIFIED
UNCLASSIFIED
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Farida AE
Twitter Followers: 1,001
Reactions Generated: 507
Reactions per 1K followers: 506
2UNCLASSIFIED
UNCLASSIFIED
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Maged Butter
Twitter Followers: 281
Reactions Generated: 487Reactions per 1K followers: 1,733
2UNCLASSIFIED
UNCLASSIFIED
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Ahmed Fouad
Twitter Followers: 529
Reactions Generated: 1,229Reactions per 1K followers: 2,323
2UNCLASSIFIED
UNCLASSIFIED
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You say you want a revolution Wael Ghonim
Twitter Followers: 86,000+
Reactions Generated: 3,291
Reactions per 1K followers: 38
2UNCLASSIFIED
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How do we do this?
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NCLASSIFIED
Identify Activate Measure
Gather massive amounts ofdata from postings,
comments, and tweets in
real-time (or any other
web/enterprise data
source).
Identify relevant Mass
Influencers
Engage Mass Influencersthrough:
Information Operations
(government)
Marketing Campaign
(commercial)
Grassroots Activation
(political)
Measure the impact of the
campaign engagement,
sales, sentiment, conversion,
donations, etc..
Measure message cascades,
diffusion, volume andcorrelate to offline events
UNCLASSIFIED
DeepMile uses Agent209, a proprietary
social influence tool to identify, activate and
measure influencers
UNCLASSIFIED
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Looking Up the Magicians Sleeve
Continuous Data Collection EntireTwitterverse and other Targeted SocialMedia (Blogosphere, etc.)
3UNCLASSIFIED
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Continuous
CollectionNarrow-Deep100% of narrow slices
Wide-Shallow3-5% of
EVERYTHING
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What do we have?
~ 500 million tweets, wide-shallow Up to 12 months of history in wide-
shallow
3-5 million tweets a day, deep-narrow(for short periods of time)
~50 million user profiles (30% of activeTwitter users)
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Social out-reachers Where conversationsoccur
Provide targetedcontent Drive to action
But there are millions of
conversations!
Agent 209
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M ti t i d th i
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Map conversation topics and theirrelationships to each other extracting onlyrelevant conversations
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Looking Up the Magicians Sleeve
Map information diffusion processesspread of ideas influence
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Looking Up the Magicians Sleeve
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Looking Up the Magicians Sleeve
Advanced geo-location of tweets andcorrelation to in-market events and news
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Diffusion Curves
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Diffusion of Hashtags
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NCLASSIFIED
There are but two powers in
the world, the sword and the
mind. In the long run the
sword will always be beaten
by the mind.
- Napoleon Bonaparte
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We have the
best congressmoney can
buy(Mark Twain)
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Campaign Finance People can donate money to directly to
candidates, but not more then $2500
People and corporations can donatemoney to Political Action Committees(PACs)
PACs spend money to supportcandidates
There is not limit, but they have to reportit
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What are PACs
Same or almost same as lobbyists
Some PACs are single-candidate, butmost big ones support many candidates
National Rifle Association
AFL-CIO PAC National Right to Life
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2-mode network PAC ----spends-$-for----> Candidate Valued network, value of links = $$
Bipartite graph In-degree centrality = received more
support
Out-degree centrality = spends a lot toadvance a certain agenda, or ishedging bets
F 2 d t 1
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From 2-mode to 1-
mode
PAC
Candidate
PAC
Candidate
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Methodology
Federal Election Commission recordsfor 2000
900 candidates, 4000 PACs, 2.5 mildonations
Use SQL to compute 1-mode networks
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No more business as
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No more business as
usual
#TeaParty -- 2009 #occupywallstreet
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