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An Agent-Based Simulation
of Viral Marketing Effects in
Social Networks
Axel Hummel1, Heiko Kern1, Stefan Kühne1 and Arndt Döhler2
1 Business Information Systems, University of Leipzig 2 Intershop Communications AG
ESM'2012 –
26th European Simulation
and Modelling Conference
Outline
Introduction
Simulation model
The Facebook domain
Model structure
Behaviour of the agents
Simulation results
Conclusion and future work
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Motivation
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Source: http://www.squaremartinimedia.com/wp-
content/uploads/2010/10/facebook-friends-box.jpg
Social networks
connect friends
Interesting news are
send to the friends
Viral effects provide
new marketing
possibilities Source: http://lh4.ggpht.com/-
W1j4mm_HymI/Tem3N0f_B1I/AAAAAAAAB2o/l6TIAiPd
mvU/Viral-Marketing%2525255B4%2525255D.png
Problem
Axel Hummel 4 22.10.2012
Companies have a lack of
experience with social networks
They do not know how to use social
networks for viral marketing
Return on investment calculation
is a challenging task [1]
? ? ?
Solution
We use agent-based simulation to forecast
the effects of marketing campaigns
The goal of the simulation is to answer the
following questions
1. How many Facebook fans are expected?
2. What are the benefits for the online shop?
3. What costs are incurred?
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The Facebook domain
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User
Company
User
User
User
User
isFriend ►
isFriend ►
The Facebook domain
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User
Company
User
User
User
User
isFriend ►
isFriend ►
The Facebook domain
Axel Hummel 8 22.10.2012
User
Company
User
User
User
User
isFriend ►
The Facebook domain
Two main requirements for the simulation
model
(1) Representation of the individual
friendship relationships
(2) Modelling of the communication process
between
A company and its fans
The Facebook friends
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Overview of the model structure
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onlineActivity : OnlineActivityuserType : UserTypeisRegularCustomer : Boolean
regularCustomerBecomeFan : DoublememberBecomeFan : DoubleperceptionProbabilityNewsfeed : DoubleclickThroughRate : Double
<<agent>>User
name : StringadvertisementActivity : IntegersetupCosts : DoublecostsPerFanPageUpdate : Double
<<agent>>Company
type : NewsTypetime : Integer
News
hasFriends
*
isFriend
*
NewsFeed
*
1
1
0..1
* hasFans
isFanOf
1
* sentNews
isSentBy
1
sentNews
isSentBy*
User agent
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onlineActivity : OnlineActivityuserType : UserTypeisRegularCustomer : Boolean
regularCustomerBecomeFan : DoublememberBecomeFan : DoubleperceptionProbabilityNewsfeed : DoubleclickThroughRate : Double
<<agent>>User
name : StringadvertisementActivity : IntegersetupCosts : DoublecostsPerFanPageUpdate : Double
<<agent>>Company
type : NewsTypetime : Integer
News
hasFriends
*
isFriend
*
NewsFeed
*
1
1
0..1
* hasFans
isFanOf
1
* sentNews
isSentBy
1
sentNews
isSentBy*
Behaviour of the user agent
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Log in
Read news feed
Press
fan button?
Want to visit
Facebook?no
yes Is regular
customer?no
yes
Visit
online shop?
Press
like button?
Log out
Press
fan button?
[!pONCE, if onAc = ONCE][!pSEVERAL, if onAc = SEVERAL]
[false, if onAc = DAILY]
[true, if onAc = DAILY][pSEVERAL, if onAc = SEVERAL][pONCE, if onAc = ONCE] [isRegularCustomer = true]
[isRegularCustomer = false]
Press
fan button
yes
no
[regularCustomerBecomeFan]
[!regularCustomerBecomeFan]
[isFan = false] and
[isFan = true] or
Press
like button
[userType = ACTIVE_USER]
[userType = LURKER]
Press fan
button
yes
[memberBecomeFan]
[!memberBecomeFan]
[isFan = false] and
[isFan = true] or
Visit
online shop
yes
no
[clickThroughRate]
[!clickThroughRate]
[visitShopThisDay = false] and
[visitShopThisDay = true] or
[feed is empty] [feed is not empty]
[NewsType = FRIEND_NEWS]
[NewsType = COMPANY_NEWS]
Every message is read with a probability of perceptionProbabilityNewsfeed,otherwise a message is ignored.
yes
no
no
Behaviour of the user agent
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Log in
Read news feed
Press
fan button?
Want to visit
Facebook?no
yes Is regular
customer?no
yes
Visit
online shop?
Press
like button?
Log out
Press
fan button?
[!pONCE, if onAc = ONCE][!pSEVERAL, if onAc = SEVERAL]
[false, if onAc = DAILY]
[true, if onAc = DAILY][pSEVERAL, if onAc = SEVERAL][pONCE, if onAc = ONCE] [isRegularCustomer = true]
[isRegularCustomer = false]
Press
fan button
yes
no
[regularCustomerBecomeFan]
[!regularCustomerBecomeFan]
[isFan = false] and
[isFan = true] or
Press
like button
[userType = ACTIVE_USER]
[userType = LURKER]
Press fan
button
yes
[memberBecomeFan]
[!memberBecomeFan]
[isFan = false] and
[isFan = true] or
Visit
online shop
yes
no
[clickThroughRate]
[!clickThroughRate]
[visitShopThisDay = false] and
[visitShopThisDay = true] or
[feed is empty] [feed is not empty]
[NewsType = FRIEND_NEWS]
[NewsType = COMPANY_NEWS]
Every message is read with a probability of perceptionProbabilityNewsfeed,otherwise a message is ignored.
yes
no
no
Behaviour of the user agent
Axel Hummel 14 22.10.2012
Log in
Read news feed
Press
fan button?
Want to visit
Facebook?no
yes Is regular
customer?no
yes
Visit
online shop?
Press
like button?
Log out
Press
fan button?
[!pONCE, if onAc = ONCE][!pSEVERAL, if onAc = SEVERAL]
[false, if onAc = DAILY]
[true, if onAc = DAILY][pSEVERAL, if onAc = SEVERAL][pONCE, if onAc = ONCE] [isRegularCustomer = true]
[isRegularCustomer = false]
Press
fan button
yes
no
[regularCustomerBecomeFan]
[!regularCustomerBecomeFan]
[isFan = false] and
[isFan = true] or
Press
like button
[userType = ACTIVE_USER]
[userType = LURKER]
Press fan
button
yes
[memberBecomeFan]
[!memberBecomeFan]
[isFan = false] and
[isFan = true] or
Visit
online shop
yes
no
[clickThroughRate]
[!clickThroughRate]
[visitShopThisDay = false] and
[visitShopThisDay = true] or
[feed is empty] [feed is not empty]
[NewsType = FRIEND_NEWS]
[NewsType = COMPANY_NEWS]
Every message is read with a probability of perceptionProbabilityNewsfeed,otherwise a message is ignored.
yes
no
no
Behaviour of the user agent
Axel Hummel 15 22.10.2012
Log in
Read news feed
Press
fan button?
Want to visit
Facebook?no
yes Is regular
customer?no
yes
Visit
online shop?
Press
like button?
Log out
Press
fan button?
[!pONCE, if onAc = ONCE][!pSEVERAL, if onAc = SEVERAL]
[false, if onAc = DAILY]
[true, if onAc = DAILY][pSEVERAL, if onAc = SEVERAL][pONCE, if onAc = ONCE] [isRegularCustomer = true]
[isRegularCustomer = false]
Press
fan button
yes
no
[regularCustomerBecomeFan]
[!regularCustomerBecomeFan]
[isFan = false] and
[isFan = true] or
Press
like button
[userType = ACTIVE_USER]
[userType = LURKER]
Press fan
button
yes
[memberBecomeFan]
[!memberBecomeFan]
[isFan = false] and
[isFan = true] or
Visit
online shop
yes
no
[clickThroughRate]
[!clickThroughRate]
[visitShopThisDay = false] and
[visitShopThisDay = true] or
[feed is empty] [feed is not empty]
[NewsType = FRIEND_NEWS]
[NewsType = COMPANY_NEWS]
Every message is read with a probability of perceptionProbabilityNewsfeed,otherwise a message is ignored.
yes
no
no
Behaviour of the user agent
Axel Hummel 16 22.10.2012
Log in
Read news feed
Press
fan button?
Want to visit
Facebook?no
yes Is regular
customer?no
yes
Visit
online shop?
Press
like button?
Log out
Press
fan button?
[!pONCE, if onAc = ONCE][!pSEVERAL, if onAc = SEVERAL]
[false, if onAc = DAILY]
[true, if onAc = DAILY][pSEVERAL, if onAc = SEVERAL][pONCE, if onAc = ONCE] [isRegularCustomer = true]
[isRegularCustomer = false]
Press
fan button
yes
no
[regularCustomerBecomeFan]
[!regularCustomerBecomeFan]
[isFan = false] and
[isFan = true] or
Press
like button
[userType = ACTIVE_USER]
[userType = LURKER]
Press fan
button
yes
[memberBecomeFan]
[!memberBecomeFan]
[isFan = false] and
[isFan = true] or
Visit
online shop
yes
no
[clickThroughRate]
[!clickThroughRate]
[visitShopThisDay = false] and
[visitShopThisDay = true] or
[feed is empty] [feed is not empty]
[NewsType = FRIEND_NEWS]
[NewsType = COMPANY_NEWS]
Every message is read with a probability of perceptionProbabilityNewsfeed,otherwise a message is ignored.
yes
no
no
Company agent
Axel Hummel 17 22.10.2012
onlineActivity : OnlineActivityuserType : UserTypeisRegularCustomer : Boolean
regularCustomerBecomeFan : DoublememberBecomeFan : DoubleperceptionProbabilityNewsfeed : DoubleclickThroughRate : Double
<<agent>>User
name : StringadvertisementActivity : IntegersetupCosts : DoublecostsPerFanPageUpdate : Double
<<agent>>Company
type : NewsTypetime : Integer
News
hasFriends
*
isFriend
*
NewsFeed
*
1
1
0..1
* hasFans
isFanOf
1
* sentNews
isSentBy
1
sentNews
isSentBy*
Behaviour of the company agent
Axel Hummel 18 22.10.2012
Update fan page
Want to update fan page?
no yes
[day % ad != 0] [day % ad = 0]
Model configuration
3 groups of input parameters
Company-specific parameters
Advertisement activity, setup costs, …
Facebook-specific parameters
Daily online rate, lurker rate, …
Social structure of the user agents
Facebook sub network of the University of
Pennsylvania [2]
41,554 users, 1,362,229 friendship relations
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Simulation results – growth of
Facebook fans (365 days, 10 runs)
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0
1000
2000
3000
4000
5000
6000
7000
8000
9000
0 25 50 75 100 125 150 175 200 225 250 275 300 325 350
Nu
mb
er
of
fan
s
Days
Growth of Facebook fans
Overall fans (average case) Regular customer fans (average case)
Overall fans (worst case) Overall fans (best case)
Simulation results – different
advertisement strategies
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0
5000
10000
15000
20000
25000
30000
35000
never every 14 days every 7 days every 3 days every day
Number of fans 4727 4956 5070 5390 6050
Number of shop visits 635 1099 1490 2631 6397
Overall costs (in €) 3000 4950 6900 12075 30375
Number of fans Number of shop visits Overall costs (in €)
Message time interval
Costs per Facebook fan &
costs per online shop visit
Axel Hummel 22 22.10.2012
0 €
1 €
2 €
3 €
4 €
5 €
6 €
never every 14 days every 7 days every 3 days every day
Costs per Facebook fan and costs per online shop visit
Costs per Facebook fan (€) Costs per online shop visit (€)
Message time interval
Conclusion
Number of Facebook fans and number of
shop visits depend on the message time
interval
A continuous stream of visitors requires
high Facebook activities
This results in high costs
Axel Hummel 23 22.10.2012
Summary
Agent-based simulation technique is
applied to the social networks domain
Model is calibrated and validated by real
data and the outcome of several studies
Online shop managers can optimize their
Facebook marketing activities
Axel Hummel 24 22.10.2012
Future work
Limitations
Special marketing events are not considered
(advertisements, prize competitions, …)
The decrease of fans is excluded
Other topics
Refinement of user relationships and their
influence on the user behaviour (trust model)
Refinement of the EdgeRank Algorithm
Axel Hummel 25 22.10.2012
References
[1] Intershop Communications AG, 2011. SimProgno study:
Decision Support in E-Commerce.
URL: http://simprogno.de/downloads/Auswertung_Simprogno_Studie_2011.pdf.
(in German).
[2] Traud A.L.; Mucha P.J.; and Porter M.A., 2011. Social
Structure of Facebook Networks. CoRR, abs/1102.2166.
Axel Hummel 26 22.10.2012
Thank you for your attention!
Contact information:
Axel Hummel
Business Information Systems
University of Leipzig
Augustusplatz 10
04109 Leipzig, Germany
phone: +49 341 9732303
hummel@informatik.uni-leipzig.de
http://bis.informatik.uni-leipzig.de/AxelHummel
The SimProgno Project
http://www.simprogno.de
Funded by the German Federal
Ministry of Education and Research
Axel Hummel 27 22.10.2012
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