This document explores the initiation of network effects within Facebook through a non-automated experiment using a fake profile to analyze social network dynamics from a creator's perspective. The study demonstrates that a constructed social network can achieve a critical mass, leading to cumulative friend requests and illustrating the importance of certain nodes as multipliers for network growth. Future analysis is suggested to further investigate the roles of adopters and the impact of network externalities in social settings.

1. Initiating a Network Effect in a
Social Network
Nasri Messarra – Anne Mione
17th EURAS Annual Standardization Conference
Kosice, Slovakia, 2012

2. Initiating a Network Effect in a
Social Network
• Can we initiate network effects on
the Facebook social network in a
non-automated experiment under
controlled environment?
Nasri Messara – Anne Mione
• How to put into evidence network
effects in a social network?

3. Objectives
Recent studies have focused on social network analysis suggesting
different methods to measure the density and activity of these
networks but also the role of the individuals as nodes and hubs, as well
as their centrality within these networks (Lazega, 2007; Wasserman &
Faust, 1994; Krackhardt, 1995, 1993). These studies allow us to
understand the workings of a network and the behavior of its
members, but they adopt a descriptive and analytical approach,
following Granovetter’s social approach (1974, 1985, 2000). They
examine established networks in adopting the position of observers.
We intend to explore the construction and development of a social
network from the perspective of its creator, in a strategic
entrepreneurial perspective. This posture supposes to handle specific
questions: what about the creator’s intervention? Can a social network
reach a critical mass allowing it to sustain itself and increase in size
without further intervention?

4. The Experiment
We created a fake unattractive profile on Facebook:
Man, over 40, married with children, doesn’t reply,
doesn’t post messages or photos, etc. (most Facebook
fake profiles are young attractive women with a lot of
photos, message postings, etc.)
0
200
400
600
800
1000
13-16 22 30 40 50
Average Facebook Friends by Age

5. The Befriending Strategy
• Using the “people you may know” or “mutual
friends” feature in Facebook
• Sending requests to public
figures (TV broadcasters, public
figures, etc.) of second category.
• Other fake profiles experiments* have been
conducted by other researchers but they used “bots”
(automated scripts) to send friend requests. Our
method, which is completely manual, tries to focus
on the importance of the “nodes” or friends as a
catalyst in the network growth.
* Boshmaf, Muslukhov, Beznosov & Ripeanu (2011) at the University of Columbia

6. Network Effects Set Off
Friends acceptance over time (cumulative) and friends
request (network effects take off)

7. The multiplier role : a determinant
actor in the network
Spartacus
Zeina
Tahan Tarek-
Gabriel
Sikias
Michel
Hassoun
Asma
Andraos
Nagi
Gemayel
Ramia
Midani
Youssef
Mallat
Elie Kehde
Omar
Boustany
Tania
Bechara
Jad Habib
Fady
Salamoon
Joumana El-
Khoury
Raymond
Yazbeck
Denise
Chamassian
Roy
Ferneini
Carl BerKoff
# First Name Friends Friends of
Friends
Friends of Friends of Friends
1 Ahmad 0 0 0
2 Asma 133 2960 5514
3 Assaad 54 985 2937
4 Eileen 11 182 724
5 Farah 0 0 0
6 Ghassan 0 0 0
7 Hani 28 1356 8185
8 JeanMarc 50 885 2487
9 Joumana 34 1797 8658
10 Nadine 17 704 6615
11 Nasri 12 540 6256
12 Omar 176 5396 8402
13 Patricia 13 169 725
Some nodes (or friends) on the network will encourage
other people to accept friends request, whereas, some
of them, will bring no friends but themselves.
Detecting these “multipliers” within the network can
bring more understanding and control of the network.

8. Analyzing Social Network
Future analysis will take into consideration the imbrication of Networks and the
Time (precedence) variable

9. Results
• We created a social network to an inexistent person and reached a
critical mass where, through externalities, our fake profile started
receiving friend requests without any action or reaction from his
end.
• This experiment also showed that network externalities, as
developed by Katz and Shapiro (1985) for several types of networks,
may be applied to social networks with all the benefits associated
to such networks, and that an entrepreneur can have better control
over social networks than over non-virtual networks.
• We have also shown how the number of adherents and the role of
the first adopters are determinant. We have demonstrated that this
network has strong and weak nodes and how some of the users can
have dangerous repercussions on the whole network.

10. Discussion
• In this experiment, the nature and role of the adopters
are examined. A next step of the experimentation can
be to interview the adherents. We can also announce
professional, commercial, or personal events to specific
people within the network, on a multiplier path or
outside it, and measure the reaction on the network.
• A lot remains to be analysed and automation using
accurate and powerful software tools should be
investigated. This experiment does not answer all the
questions asked but opens a door for a more thorough
and quantitative analysis.