HARNESSING AI FOR ENHANCED MEDIA ANALYSIS A CASE STUDY ON CHATGPT AT DRONE EM...
Information cascades
1. Social Networks
Information Cascades and
Viral Marketing
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2. Which
restaurant to
choose?
conformity
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3. Information cascade
making the same decision that the others have
made, independently of the own private
information signals
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4. Information cascade
Sequential decision making
Incomplete information
The choice of previous participants is known
(but no the reasons!)
Limited selection space
Rational decision making
A posteriori probability (Bayes’ theorem)
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5. Information spread
Medium:
network structure
Model:
distribution mechanism
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6. Universal structure of
social networks
Power low degree distribution
Gigantic connected component
Small world phenomenon
Large clustering coefficient
Hierarchical structure
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7. Diffusion model
method - diffusion
virus model
“infected” on contact
probability depends on
immunity
can model
news
gossips
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12. Diffusion model
Step 5
Complete coverage
Process time depends
on the source
Based on connectivity
pattern
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13. Threshold model
neighbors “opinion”
decision threshold
information cascade
can model
beliefs propagation A,B - types of behavior
purchasing decisions q –decision threshold
spread of innovations If fraction of neighbors with A
greater than q, accpet A
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18. Threshold model
Step 4
incomplete cascade
depends on network
topology
strongly depends on
source selection
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19. Complete cascades
Strategic source placement
Well connected
Inside various communities
Increase of competitive advantage
reduce threshold level
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20. “The Dynamics of Viral
Product recommendation network
Marketing”
J. Leskovec et al, 2007
(DVDs)
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21. #newsjp
Twitter
retweet #ocra
mention
“Truthy” Project. Center for Complex Networks and System
Research. Indiana University.
#iraq
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