this is my final thesis book, on "Business Model Innovation: Narratives building Business Logic. The social network case". the whole work is divided into three parts: research (on Business Model and Social Network), analysis (longitudinal of Facebook, Twitter and google+ on different levels-logic, narratives, product), and project (the remodel of the Vodafone community Youniversity) it's the beginning of a meta-design research

1. “non le connessioni oggettive delle cose, ma le connessioni concettuali dei
problemi stanno a base dei campi di lavoro delle scienze: allorché viene
affrontato con nuovi metodi un nuovo problema e vengono in tal modo
scoperte verità che aprono nuovi punti di vista significanti, allora sorge una
scienza”
M. Weber

2. cover page image by J. Thorpe

3. BUSINESS MODEL INNOVATION
Narratives shaping Business Logic
The Social Network case
M. CHIARA CACCIANI
PSSd master thesis
Politecnico di Milano
Facoltà del Design
A.A. 2009-2011
749212
thesis tutor Cabirio Cautela
m.chiara.cacciani@gmail.com

5. 1. INTRO

7. INTRODUCTION
- Aknowledgments
If you are reading those lines it means that I actually made it!
I’m either graduating in this moment or I’m a Politecnico di
Milano alumni; either way I’d like to thank who helped me real-
ize this.
To Cabirio Cautela for believing in me from the beginning,
having the time, and the patience to keep me on track and for
always showing me the flip side of the coin. It has been a very
challenging and rewarding path, thank you for sparking my
creativity.
To Matteo Gemignani for having walked side by my side for
those five years, for giving me the freedom to learn by doing,
supporting all of my choices even if they brought me on the
other side of the world.
To all of my PSSDers, because I truly feel lucky I was part of
the 2011 class: a vibrant mix of motivation, competition, intui-
tion, passion and talent for designing. Today a special thought
goes in particular to Valeria Adani, Gustavo Primavera, Miguel
Bello, Angelica Bello and Ana Isabel Palacios for being guides,
friends and inspiration in those two years together.
Last but not least, to my family who supported me in this
whole path, spoiling me with more than what I could have ever
needed, lately even providing me with “an office” to foster my
concentration and finalize my thesis.
7

8. INTRODUCTION
- Table of Contents
Introduction
Abstract
1. English version 10
2. Italian version 11
Methodology 12
Objective 12
Research
2.1 Business Model Generation
Why Business Model? You’re a designer! 16
A recent discipline 17
A definition in evolution 17
Business Model – The new unified perspective 18
1. Building Blocks 18
2. Taxonomies 19
3. Ideal type 19
4. Performative Representation 20
Business Model – conclusion 22
2.2 Social Network
Why this case study 24
Not a new concept 25
Components and types 26
Online networks 31
2004 the boom 32
Typologies 34
Analysis
3.1 Three case studies
Hypothesis 39
Methodology 40
3.2 Facebook – history 44
2004 46
2005 49
2006 52
2007 56
2008 61
2009 66
2010 72
2011 78
Longitudinal evolution and conclusion 84
3.3 Twitter – history 93
2006 94
2007 99
2008 103
2009 108
2010 118
2011 124
Longitudinal evolution and conclusion 128
3.4 Google+
A limit case study 134

9. History 135
June 136
July 142
August 147
September 152
October 156
Conclusion 160
3.5 Compared conclusion 164
CVD (ComeVolevasiDimostrare) – preliminary remarks
confirmed 166
Project (Let’s Re-Model)
4.1 Intro
“Re-modeling” Youniversity 169
The methodology 169
4.2 Context: Vodafone
Intro 170
History 170
Vodafone Italy: history 172
Vodafone Italy: Employer Branding and Recruiting 173
4.3 Youniversity
Intro 174
The Golden RIBS 175
Business Logic 177
Business&Users Narrative 179
The platform evolution 185
The employer branding business model 187
4.4 Re-modeling
The Employer Branding Narrative System 189
The value proposition 190
Vodafone E.B. customer segment 190
Avoiding risks: the missing student and recruitment 193
The new Employer Branding Narrative 194
The new Business Logic 197
The multi-channel strategy 198
Youniversity channel intra-connection 199
Youniversity new RIBS 204
The Employer Branding interconnected channel system 205
5. Conclusion
Final consideration on the work 209
Appendix
User Narrative Survey 212
Bibliography 214
Webliography 216
Videography 222
List Of Figures 222
9

10. INTRODUCTION
1.1 Abstract
- English version
“Business Model Innovation: Narrative shaping the Logic” is
a meta-design research oriented to provide evidences of the
validity of the narrative business model approach, and prove
the trans disciplinary value of PSS practice and tools, ultimately
of the design discipline.
The research is based on previous scholars’ work on the defini-
tion and possible application of Business Models as narratives.
This perspective considers Business Model beyond their func-
tional value, as descriptors of the business logic, to interpret
them as “stories, that explain how the enterprise works” (Ma-
gretta). The goal would be to present evidence of the meaning
generation power of those narratives, it is in the encoding and
decoding communication process that messages can evolve and
assume new meanings created in a crowd sourced way. For this
crowd sourcing aspect I thought to select as analysis context
social networks, probably an extreme example of this theory.
The work is structured in three parts:
The research
In the first part I collected and clustered different business
model and social network literature schools, with particular
focus on the Business Model narrative approach.
The analysis
The second part is a longitudinal analysis of Facebook, Twitter
and Google+. I selected those three social networks because
they are the current major generalist social networks and/or
with greater growth potential.
The analysis is based on observing the social network evolution
on three levels: business logic, narratives (business, user and
market narratives) and platform; aiming to detect how those
three levels interact and ultimately to analyze how the meaning
generation process is built.
The application: remodeling Youniversity
In the third and last part, I remodel Youniversity, an existent so-
cial network by Vodafone, currently not satisfying the purpose
it was created for, with a business model narrative approach,
guided by the insights I had gathered during the research and
analysis phase.

11. INTRODUCTION
1.1 Abstract
- Italian version
“Business Model Innovation: Narratives shaping Business
Logic” è una tesi di ricerca nell’ambito del meta-design, che
basandosi sulla recente letteratura di business model genera-
tion, in particolare su quella scuola che vede la business model
narrative come uno strumento di generazione di nuovi signifi-
cati; si propone di verificarne la potenzialità dei meccanismi di
comunicazione e di costruzione di significati nella narrazione
nello specifico ambito dei social network.
Infatti nel momento stesso in cui un’azienda comunica ai suoi
clienti direttamente o indirettamente, sta creando una rappre-
sentazione di se portatrice di un duplice significato: quello sog-
getto principe della comunicazione e quello racchiuso nella mo-
dalità scelta per la comunicazione, esempi di quest’ultimo sono
il lessico, il tono, il mezzo di comunicazione scelto. Un terzo
aspetto da considerare, e particolarmente rilevante rispetto al
caso studio scelto, è la decodificazione del messaggio da parte
dei riceventi; infatti, in questo processo è racchiusa un’ulteriore
possibilità di significazione corale. Per questa caratteristica cor-
ale ho selezionato come caso studio i social network, in quanto
rappresentano l’esempio limite, e quindi spero più significativo.
Il lavoro è strutturato in tre parti:
Ricerca
La prima parte è dedicata ad una panoramica della letteratura
sui business model, con particolare dettaglio per la scuola di
pensiero che interpreta i business model come narrazioni, ed
una sui social network. Il concetto di social network infatti,
nonostante sia diventato di dominio di massa con MySpace
e Facebook è originariamente un concetto legato alle scienze
statistiche e sociali, usato come strumento di analisi sociale. È
tornato utile ai fini progettuali ricercare questi originari concetti
base.
Analisi
La seconda parte è quella dedicata ad un’analisi longitudinale
dei tre social network maggiori in termini di base utente e/o
considerati dagli esperti con maggior potenziale; ovvero Face-
book, Twitter e Google+.
L’analisi è stata condotta analizzando anno per anno ogni social
network su tre livelli paralleli: business logic, narrative (lato
business, lato utenti e lato mercato) e il prodotto (la piattaforma
web). Il fine ultimo è di capire come i tre livelli interagiscono tra
loro e le dinamiche del processo di significazione proprio delle
“storie” espresse dal business e dagli utenti (e come rappresen-
tato sulla piattaforma).
Applicazione: il progetto
La terza ed ultima parte è dedicata a mettere in pratica le di-
namiche individuate nella fase di analisi, re-modellando Youni-
versity, un social network privato di Vodafone, che al momento
non genera il valore, e quindi i significati, aspettati.
11

12. INTRODUCTION
1.2 Metodology of Research
Business Model literature is still a fuzzy field; scholars are still
debating about what the definition is, and what role business
model can have in the future.
Firstly I dipped myself into the literature trying to read enough
literature about Business Models to have the most complete
image I could. Same thing I did for social network; in fact
although I’m a Facebook addicted, I often tweet and I’m check-
ing my Google+ page daily, I didn’t really know much about
how they evolved since their launch or about their business
model; along with a research in social network literature form
the ’50s, when this discipline was developed in sociology, psy-
chology and anthropology.
Developed a sufficient knowledge about the two research fields
I selected, I was able to define a thesis hypothesis to be tested
in the analysis phase.
In this second phase I used a longitudinal analysis approach I
explain in detail in chapter 3.1., to gather evidences that could
support and prove my hypothesis.
Ultimately to deeply interiorize my findings I decided to apply
them to a project: I remodeled Youniversity, a social network
by Vodafone, according to the strategic business narrative
approach I had tested and I believe it can help generate new
significant meanings.
INTRODUCTION
1.3 Objectives
- Test business model narrative approach in social network
context
- Deeply understand Facebook, Twitter and Google+ business
model evolution
- Analyze social network interaction logic key drivers
- Generate awareness of the crucial role social networks have in
our meaning generation process
- Detect and take into consideration in the project ongoing
social trends
- Remodel the social network Youniversity based on analysis
findings and coherently with Vodafone Employer Branding
strategy
- Root the project into PSS tools, methods and project logics
- Propose product service system design as central player into
business model building and meaning generation
- Develop a work I can be proud of

13. 2. RESEARCH
13

15. BU S I N E SS M O DE L
G E N E R ATI O N

16. BUSINESS MODEL INNOVATION
2.1. Why Business Model? You’re a designer!
This is a question people often ask me when I try to explain
my thesis research field, and every time I can’t avoid being a bit
disappointed, since I think the connection between business
model generation and product service system design is so clear!
I’ve always admired the design discipline for its people centered
shape modeling power; through creative tools designers have
the ability and knowledge to craft products and services around
people; Bruno Munari, Vico Magistretti, Achille Castiglioni
were all inspirations. And it is probably people the variable that
makes design creation practice much more fascinating to me
than scientific one.
However today the context we are projecting for is very dif-
ferent from Munari’s era, everything is changing and will keep
changing very rapidly. There are major social, economics, cul-
tural, political and even religious trends that are yelling at us we
have to be more sustainable, that there is no place for further
objects or waste of resources. Our context is not about invent-
ing new things, but it’s about finding new meaningful ways of
combining existing parts. Deciding to take this challenge design
has to become a holistic discipline that deals with organization
and integration of services and products in the most sustain-
able and useful way as possible.
In today chaos of elements, it’s not easy to see connect the dots
and see the bigger picture and to finalize a strategy to make de-
signed scenarios coming true. Business models are cross design-
management tools to foster the creation of new meaningful
scenarios; the role of design assumes a special prominence if
we interpret business model as narratives, as “stories that ex-
plain how enterprise works”. Storytelling and visualizations are
in fact key design expertise.
This field of research is not completely new in the design
world, there is another growing design discipline: the “design
thinking” that wants to tackle similar issues, it is indeed “a dis-
cipline that uses the designers sensibility and methods to match
people’s needs with what is technologically feasible and what
a viable business strategy can convert into customer value and
market opportunity.”
In conclusion I picked business model generation as my thesis
field, because I believe it’s a good opportunity where product
service system design and management, for the systemic nature
they share, can work together to shape new meaningful sustain-
able future scenarios.

17. BUSINESS MODEL INNOVATION
2.2 Business Model - a recent discipline
The literature shows Business Model as a fuzzy topic; scholars,
in fact, are still striving for a common definition and a manner
to investigate this field.
The “Business Model” term is a relatively young phenomenon,
A. Osterwalder and Y. Pigneur pioneers of this discipline,
researched on Scholarly Reviewed Journals the term, and found
out that although it appeared for the first time in an academic
article in 1957 (Bellman, Clark et al. 1957) and in the title and
abstract of a paper in 1960 (Jones 1960) it was only towards
the end of the 1990s that it became relevant, together with the
advent of the Internet in the business world. This synchronicity
is not a chance; first in the web 1.0, now in the 2.0 one, infor-
mation technology became very cheap, allowing not only many
companies to have access to it, but blurring industries bounda-
ries. Indeed industry classification is not meaningful anymore
as unit of analysis, and that’s probably the role that fits business
model the best.
BUSINESS MODEL INNOVATION
2.2 Business Model - a discipline in evolution
A. Osterwalder and Y. Pigneur highlighted five main phases in
the evolution of the business model literature and in the search
for a proper business model definition.
schema 1
define & classify list business model describe business model business apply business
ACTIVITY
business models components model elements model elements model concept
OUTCOME
definitions & “shopping list” of components as reference models applications &
taxonomies components building blocks & ontologies conceptual tools
In a first phase, in early 2000 when the term started gaining
popularity, a number of authors suggested business model
definitions and classification an example of it is “the firm’s eco-
nomic model, concerning its logic of profit generation”1 .
In the second phase authors started to complete the definitions
by proposing what elements belong into a business model. In
this phase those lists merely mentioned descriptors of it, they
were still very superficial indeed.
1 Morris M., Schindehutte M., Allen J., 2004, The entrepreneur’s business
model: toward a unified perspective, Journal of Business Research
17

18. Only in the third phase they started doing detailed descriptions
of these components structuring and designing organizations
with them. Business models became “transaction structures”;
they described the way firms configured their transactions with
groups of stakeholders including customers, suppliers and ven-
dors: “a business model is the content, structure, and govern-
ance of transaction designed so as to create value through the
exploitation of business opportunities” (Amit and Zott, 2001)
The business model became the manifestation of how certain
organizational variables were configured and the consequences
of that configuration on business performance; this approach
is well known also as building blocks theory. Consequently
various business model taxonomies were generated, such as the
“efficiency centred” and “novelty centred” by Zott and Amit.
In the fourth phase researchers started to model the compo-
nents conceptually, proposing business model as meta-models
in the form of reference models and ontologies. Business mod-
els as well as their elements became “ideal types”, references to
cluster and define businesses.
The last phase, the current one, is the one in which reference
models are being applied in management. Scholars are now
testing in different fields, if the application of business model,
can create a significant competitive advantage. Moreover which
are the best conceptual tools and application fields.
BUSINESS MODEL INNOVATION
2.3 The new BM unified perspective
In conclusion, scholars’ contributions on the definition of busi-
ness models can be classified in four different categories; I’ll
shortly go through the first two to then explain more exhaus-
tively the last ones.
1. Building-blocks
First, Business Model are conceptualization of a particular
real world business model: this is the building-blocks perspec-
tive, oriented to define the main blocks that create and capture
value, the so called “business logic”. Osterwalder and Pigneur
(2010) finalized a great tool to visualize the nine blocks that
constitute the business logic, as they assert the communication
power of business model crucial and worth to research on.
This first conception is focused in particular on e-businesses,
and tries to create and capture value from a given technology.
In this domain, researchers have identified four possible “value
streams” in an internet-based business: virtual communities,
reduced transaction costs, exploitation of information asymme-
try, and value-added market-making process.

19. 2. Taxonomies
There is a group of authors that describe business models as
classifications, distinctive abstract types of business models,
each one describing a set of business with common charac-
teristics. In this sense business models are taxonomies, classes
of things observed in the world and developed from empirical
work, bottom up; they are both a scale and a role model, like
scale models they represent descriptions not too general nor
detailed of firms, but at the same time they individuate a set
of known business models based on generic kinds of behavior
which are distinctly different; they serve as role models that
scholars use to cluster individual firms.
Thanks to this double scale-role model function, according to
Banden-Fuller and Morgan, business models seem to be the
perfect environment for experimentation, to conduct the same
testing that biologist do with their model organism when they
check their theories against behavior in the world, to see how
far the findings match the characteristics of the real world the
their models purport to represent. Business models are to man-
agement real-life examples to study and apply, in fact a collat-
eral use of business model ideal type is as typification. This idea
is associated with the role model nature described before that
identify business model as well known categories and external
identity that a firm can assume (Polos et al., 2002). This con-
cept can be particularly relevant applying it to nascent markets,
where there is little certainty about values associated with new
ventures, firms in those situations strive to render themselves
identifiable and legitimate and associating themselves with ideal
business models can be a solution.
3. The ideal type
Another business model definition is as abstract overarch-
ing concept that can describe all real world businesses. This
concept can be associated with Max Weber’s “ideal type”.
“Business models might be understood as ideal types, for they
seem to have the characteristics and fulfill the roles that Weber
associated with such types: they are based on both observation
and theorizing”
The parallel that C. Baden-Fuller and M. S. Morgan create
between business model and the Weberian concept of “ideal
type” is fundamentally based on the double nature of the two
tools as describer of the reality and as representation of a con-
ceptual idea at the same time; it’s worth exploring the full mean-
ing of “ideal type”, to better understand why this concept can
be borrowed to enrich the definition of what business model
are and are useful for.
Max Weber (Stanford Encyclopedia of Philosophy plato.
stanford.edu) besides being an economist, a politician and an
historian is one of the principal architects of modern social
science; his methodological contribution is the most interesting
part of his research for the purpose of this thesis.
Weber’s methodology is as ethical as it is epistemological; and
that’s the interesting trait for this research, in fact ethic issues
imply a judgment and meaning attribution process.
Weber’s methodology is an attempt to give researchers tools to
judge and give meaning to objects, facts and situations; his sig-
19

20. nification process is based on the concept of “ideal type” which
is “formed by the one-sided accentuation of one or more
points of view and by the synthesis of a great many diffuse,
discrete, more or less present an occasionally absent concrete
individual phenomena, which are arranged according to those
one-sidedly emphasized viewpoints into a unified analytical
construct. In its conceptual purity, this mental construct cannot
be found empirically anywhere in reality, it is a utopia.”2
In synthesis Weber is saying that the analytical construct of an
ideal type never exists in reality, but provides objective bench-
marks against which real-life constructs can be measured sci-
entifically. In this sense the ideal type is not an end but a mean
created by gathering multiple points of views and facts, then
unified by a utopic synthesis that ultimately serves as reference.
By comparing the reality to the ideal type, relating the empiri-
cal data to an ideal limiting case, we create unambiguously
significance and a mental model that codify some key causal
relationships in the business. A business model as ideal type is a
“cognitive map” that tends to never be set in reality but provide
ongoing inspiration for improvement and change.
4. Performing representation and narratives
The last business model category is quite a new school of
thought, scholars define it as narrative or performative reprep-
resentation, “in that business model is a text that re-describes
and re-constructs reality and the social world in its own image”
(M. Perkmann, A. Spicer).
Narratives are a genre of text that describe a sequence of
events; for a firm to embrace a business model as a narrative
means to construct a representation of how it might succeed
in a particular environment through both a textual and/or a
visual images. The power of representations hasn’t been fully
explored yet, however it has the potential to literally shape
reality (and I’ll try to bring some evidences with this research);
in fact following a semiotics cycle, it first reinterprets real-
ity encoding it in a message (as M. McLuhan would say “the
media is the message”), then the receiver decodes it, filtering
and enriching the received narrative with his own point of view.
As Clarke and Hold state in an entrepreneurial research: “how
entrepreneurs select and frame individual stories, both reveals
and creates the entrepreneurial self; therefore entrepreneurs are
constituted by their narrative of experience”.
Ultimately the current enterprise “reversed” meaning genera-
tion cycle remarks the importance of this business model
interpretation. According to a canonic cycle, enterprises when
launching products and services into the market, would shape
business logic first, deducing from it a coherent business narra-
tive to communicate to the market, based on a negative market
answer changes in the business logic would be implemented,
affecting the business narrative and so on, in a one way cycle.
What’s currently happening, in a market as fast as today and
with consumers that are more and more prosumers, is that the
market answer fosters a quick business narrative change, with-
out affecting the business logic; this causes gaps and risks of
incoherence between business narrative and business logic, that
2 Weber M. Objectivity in social sciences

21. ultimately can have consequences on the image of the company
and the revenues stream. This new “reversed” meaning genera-
tion cycle sets the business narrative as crucial interpreter of
market needs and gatekeeper to the business logic.
Business narrative research is a rather young domain and it
must still prove its relevance; however scholars suggest three
main possible uses of narratives that could help managers cre-
ate new business meanings: as visualization, mediator, or com-
munication tool; it’s important to consider that the three levels
are strictly intra-connected.
Visualizing complex systems increases the degree of com-
plexity that can be handled successfully (Rode 2000); in fact
using an intuitive and universal language it often enhances an
easier identification of relevant measures to follow to improve
management.
Business models have a mediator role when they capture pow-
erful and communicative images of the business that ultimately
help different actors understand each other;
schema 2
Competitive
Forces
Legal Customer
Environment Demand
BUSINESS
STRATEGY
BUSINESS
Social MODEL Technological
environment Change
BUSINESS ITC
ORGANISATION
as well as when modeling social systems they identify relevant
elements and relationships among them, acting like a conceptu-
al bridge that helps aligning business strategy, business organi-
zation and technology.
Ultimately business models can be used as powerful communi-
cation tool, as logical consequence of their role as visualization
and mediator. This use becomes particularly important if we
consider not only actors within the firm context, but also final
users and customers as receiver of the business narrative.
In practical terms, there are various techniques to build busi-
ness narratives, such as using widely known cultural myths,
archetypical figures, scenarios and metaphors.
21

22. BUSINESS MODEL INNOVATION
2.4 Conclusion
This thesis aims to test business model considered beyond its
functional value, as “stories that explain how the enterprise
works”3 , therefore as narrative.
The meaning generation power of narrative will be tested in the
social network context trying to understand what the current
meaning generation cycle is, and the role of business narrative
in it.
Moreover it won’t only consider business narrative, but user
narrative as well. In fact the social network context can be con-
sider an extreme case study to test those theories, in which, for
the market own nature, users take active part into the develop-
ment of the business; therefore it is significant to examine their
narrative as well, and see their effect onto the business narrative
and logic.
3 Magretta J., 2002, Why Business Models Matter, Harvard Business Review

23. S O CI A L N E TWO R K

24. SOCIAL NETWORK
2.1.1 why this case study
After researching and reading on Business Model generation,
dug into the literature, theories and future scenarios, I em-
braced the theory of business model interpreted as narrative
and of its meaning generation potential as re-interpretation of
the value proposition of the Business Logic. Shaping a power-
ful Business narrative means crafting a message as clean and
direct as possible, that simply visualizes or expresses (image or
text based narrative) the value proposition indeed; a very good
example of this are Apple’s commercials.
So, why are Social Networks value proposition particularly
interesting? Social Networks are transparent models, which
means that they don’t advertise to give an image of themselves
to customer, their image is simply deducted from the service
itself, the platform indeed; this of course, makes the platform
a narrative channels. I chose it as case study for this research
because social networks create a space, a reality that enables
human communication and confront, which is, according to
semiotics, the base of our meaning generation process. We
“create” meaning through difference, and context plays a role;
our signification process takes place through a network (ironic?)
among signifier, signified and referent; and one triangle can
become the referent of another, this network of triangles is the
structure we use everyday to evaluate and give meaning to our
everyday life.
Though, if on one hand social networks value proposition is
to create contexts where users can generate meanings, on the
other one, their possibility to evolve and innovate is completely
dependent on their user base. The user narrative, not only the
business narrative, is crucial.
There is another meaningful factor: the developers case.
I consider Social Networks as a transparent company, therefore
the platform is the element they use as business narrative, but
what if there are users who can shape the platform and com-
municate through it as well? Through the APIs developers are
creating contents and modifying the platform, which is then the
place where business and users narrative meet.
In conclusion when analyzing social networks the element to
take in consideration are not only business narrative and busi-
ness logic, but also users narrative as well as the platform, key
touch point in the meaning generation system.
“The whole process of meaning generation starts and ends
with people”1 especially in this “age of transparency” in which
“what happen in Vegas stays on YouTube”2 .
Social networks are such a fascinating business case to analyze
when facing a meaning generation topic.
1 Solomon Micheal R., 1998, Consumer Behavior, Buying, Having, and Being,
4th ed., Prentice Hall (pp.270)
2 Qualman E., 2009, Socialnomics: How social media transforms the way we
live and do business. New York, Wiley (p. 47)

25. SOCIAL NETWORK
2.1.1 not a new concept
The terms Social Network is a lot older than seven years, which
is when for the first time it gained worldwide fame thank to
Facebook (2004). Social Network Analysis is inherently an
interdisciplinary topic that has been shared by mathematics,
statistics, computer methodology and social science for the
past twenty years; the first use of the term “Social Network” is
attributed to the anthropologist John Barnes (1954) indeed. Out
of all, I’ll manly focus on the social science perspective, making
some references to the mathematics one.
Social Network analysis is a distinct research perspective within
the social and behavioral sciences; distinct because it is based
on the assumption of the importance of relationships among
interacting units, instead of analyzing the single unit value
itself; encompassing theories, models and applications that are
expressed in terms of relational concepts of processes.
Pioneers of this discipline come from sociology, psychology
and anthropology; and they define a Social Network as “a
network of relations linking social entities, or of webs or ties
among social units emanating through society.”3
The last part of this definition is extremely interesting, it’s
stating that analyzing social network also provides a formal,
conceptual means for thinking about the social world; provid-
ing formal statements about social properties and processes
(Freeman, 1984), specifically about relationships among social
entities, and on the patterns and implications of these relation-
ships.
Thinking in terms of Social Network is essentially very similar
of thinking in terms of product service system.
Many researchers have realized that the network perspective
allows new leverage for answering standard social and behavio-
ral science research questions by giving precise formal defini-
tion to aspects of the political, economic, or social structural
environment. From the view of social network theory, the
social environment can be expressed as patterns or regulari-
ties in relationships among interacting units; those patterns are
defined as structure composed by nodes (units/actors) and ties
(relationships).
To fully understand the Social Network theory first we have to
understand how it interprets units and relationships, to then
have a look at the different types and dynamics.
3 Wasserman S., Faust K., 1994, Social network analysis. Methods and applica-
tions, 2nd ed., Cambridge University Press (pp.10)
25

26. SOCIAL NETWORK
2.1.3 components and types
When a computer network connects people or organizations,
it is a social network. Just as a computer network is a set of
machines connected by a set of cables, a social network is a set
of people (or organizations or other social entities) connected
by a set of social relationships, such as friendship, co-working
or information exchange.
Social network analysis reflects a shift from the individualism
common in the social sciences towards a structural analysis.
This method suggests a redefinition of the fundamental units
of analysis and the development of new analytic methods. The
unit is now the relation, e.g., kinship relations among persons,
communication links among officers of an organization, friend-
ship structure within a small group. The interesting feature of
a relation is its pattern: it has neither age, sex, religion, income,
nor attitudes; although these may be attributes of the individu-
als among whom the relation exists. . . .
Social network analysts look beyond the specific attributes of
individuals to consider relations and exchanges among social
actors. Analysts ask about exchanges that create and sustain
work and social relationships. The types of resources can be
many and varied; they can be tangibles such as goods and
services, or intangibles, such as influence or social support; the
resources are those that can be communicated to others via
textual, graphical, animated, audio, or video-based media, for
example sharing information (news or data), discussing work,
giving emotional support, or providing companionship.
Relations
Relations (sometimes called strands) are characterized by con-
tent, direction and strength. The content of a relation refers to
the resource that is exchanged.
A relation can be directed or undirected. For example, one
person may give social support to a second person. There are
two relations here: giving support and receiving support. Alter-
nately, actors may share an undirected friendship relationship,
i.e., they both maintain the relationship and there is no specific
direction to it. However, while they both share friendship, the
relationship may be unbalanced: one actor may claim a close
friendship and the other a weaker friendship, or communication
may be initiated more frequently by one actor than the other.
Thus, while the relationship is shared, its expression may be
asymmetrical.
Relations also differ in strength, and such strength can be
operationalized in a number of ways . With respect to com-
munication, pairs may communicate throughout the work day,
once a day, weekly or yearly. They may exchange large or small
amounts of social capital: money, goods, or services. They may
supply important or trivial information. Such aspects of rela-
tionships measure different types of relational strength.
Ties
A tie connects a pair of actors by one or more relations. Pairs
may maintain a tie based on one relation only, e.g., as members
of the same organization, or they may maintain a multiplex tie,
based on many relations, such as sharing information, giving
financial support and attending conferences together. Thus

27. ties also vary in content, direction and strength. Ties are often
referred to as weak or strong, although the definition of what
is weak or strong may vary in particular contexts [Marsden &
Campbell, 1984]. Ties that are weak are generally infrequently
maintained, non-intimate connections, for example, between
co-workers who share no joint tasks or friendship relations.
Strong ties include combinations of intimacy, self-disclosure,
provision of reciprocal services, frequent contact, and kinship,
as between close friends or colleagues.
Both strong and weak ties play roles in resource exchange net-
works. Pairs who maintain strong ties are more likely to share
what resources they have. However, what they have to share
can be limited by the resources entering the networks to which
they belong. Weakly-tied persons, while less likely to share
resources, provide access to more diverse types of resources
because each person operates in different social networks and
has access to different resources. The cross-cutting “strength
of weak ties” also integrates local clusters into larger social
systems.
Multiplexity
The more relations (or strands) in a tie, the more multiplex (or
multistranded) is the tie. Social network analysts have found
that multiplex ties are more intimate, voluntary, supportive and
durable. Yet some analysts have feared that email, the Internet
are unable to sustain broadly-based, multiplex relations. These
fears are extended by the boutique approach to online offer-
ings which fosters a specialization of ties within any one of
thousands of topic-oriented news groups. However, this ten-
dency toward specialization is counter-balanced by the ease of
forwarding online communication to multiple others. Through
personal distribution lists Internet participants can sustain
broad, multiplex, supportive relationships.
Composition
The composition of a relation or a tie is derived from the social
attributes of both participants: for example, is the tie between
different or same sex dyads, between a supervisor and an un-
derling or between two peers.
Beyond the Tie: Social Networks two Views: Ego-centered
and Whole Networks
A set of relations or ties reveals a social network. By examin-
ing patterns of relations or ties, analysts are able to describe
social networks. Typically analysts approach social networks in
two ways. One approach considers the relations reported by a
focal individual. These ego-centered (or “personal”) networks
provide a Ptolemaic views of their networks from the per-
spective of the persons (egos) at the centers of their network.
Members of the network are defined by their specific relations
with ego. Analysts can build a picture of the network by count-
ing the number of relations, the diversity of relations, and the
links between alters named in the network. This ego-centered
approach is particularly useful when the population is large, or
27

28. the boundaries of the population are hard to define. For ex-
ample, Wellman and associates ([Wellman, 1988a]; [Wellman &
Wortley, 1990]) used ego-centered network analysis to explore
how a sense of community is maintained through ties, rather
than through geographical proximity, among Toronto residents.
They built a picture of the typical person as having about a
dozen active ties outside of their household and workplace,
including “at least 4 ties with socially close intimates, enough
to fill the dinner table and at least 3 ties with persons routinely
contacted three times a week or more”
The second, more Copernican, approach considers a whole
network based on some specific criterion of population
boundaries such as a formal organization, department , club
or kinship group. This approach considers both the occur-
rence and non-occurrence of relations among all members
of a population. A whole network describes the ties that all
members of a population maintain with all others in that group.
Ideally, this approach requires responses from all members on
their relations with all others in the same environment, such as
the extent of email and video communication in a workgroup.
This requirement places limits on the size of networks that can
be examined.
Ego-centered and whole network views provide two ways
of examining the communication links among people: ego-
centered network analysis can show the range and breadth of
connectivity for individuals and identify those who have access
to diverse pools of information and resources. Whole network
analysis can identify those members of the network who are
less connected.
Network Characteristics
Range: Social networks can vary in their range: i.e., in their size
and heterogeneity. Larger social networks have more hetero-
geneity in the social characteristics of network members and
more complexity in the structure of these networks [Wellman
& Potter, 1997]. Small, homogeneous networks are characteris-
tic of traditional work groups and village communities; they are
good for conserving existing resources.
Centrality: it may be important to examine who is central or
isolated in networks maintained by different media. Thus, the
manager who does not adopt email becomes an isolate in the
email network while retaining a central role in the organization-
al network. Information exchanged via email will not reach this
manager while information exchanged in face-to-face executive
meetings will not reach lower-level workers. In a situation such
as this, another person may play a broker role, bridging between
the email network and the face-to-face executive network and
conveying information from one network to the other. Social
network analysis has developed measures of centrality which
can be used to identify network members who have the most
connections to others (high degree) or those whose departure
would cause the network to fall apart.
Roles: Similarities in network members’ behavior suggest the
presence of a network role. Teachers fill the same network
role with respect to students: giving instruction, giving advice,
giving work, receiving completed work, and assigning grades.
Regularities in the patterns of relations (known as structural

29. equivalence) across networks or across behaviors within a
network allow the empirical identification of network roles. For
example, the “ technological gatekeeper” is a role that may be
filled by any member of a network according to what resources
they bring in to the network.
Partitioning Networks
Groups
In social network analysis, a group is an empirically discovered
structure. By examining the pattern of relationships among
members of a population, groups emerge as highly intercon-
nected sets of actors known as cliques and clusters. In network
analytic language, they are densely-knit (most possible ties exist)
and tightly-bounded, i.e., most relevant ties stay within the
defined network. Social network analysts want to know who be-
longs to a group, as well as the types and patterns of relations
that define and sustain such a group.
Network density is one of the most widely used measures of
social network structure: i.e., the number of actually-occurring
relations or ties as a proportion of the number of theoretically-
possible relations or ties. Densely-knit networks (i.e., groups)
have considerable direct communication among all members:
this is the classic case of a small village or workgroup. Much
traditional groupware has been designed for such workgroups.
By contrast, few members of sparsely-knit networks communi-
cate directly and frequently with each other. As in the Internet,
sparsely-knit networks provide people with considerable room
to act autonomously and to switch between relationships. How-
ever, the resulting lack of mutual communication means that a
person must work harder to maintain each relation separately;
the group that would keep things going is not present.
The social network approach can also be used to see where
relations and ties cross media lines. Which kinds of groups
maintain ties via multiple media, and which communicate only
by means of a single medium? For example, a luncheon group
might coordinate meeting times through email, coordinate food
delivery by phone, with final consumption face-to-face. Other
network groups, such as remotely-located technicians, might
exchange information about only one topic and use only one
medium, such as email.
Positional Analysis
As well as partitioning social network members by groups,
analysts also partition members by similarities in the set of
relations they maintain. Such members occupy similar posi-
tions within an organization, community or other type of social
network. Those who share empirically-identified positions
are likely to share similar access to informational resources.
Some central positions have greater access to diverse sources
of information, while other positions may have a limited pool
of new ideas or information on which to draw. For example,
why assume that managers always give orders and subordinates
always take them when an analysis of email traffic may show
otherwise? Thus our study (of university computer scientists)
found that faculty did not always give orders and students did
not always receive orders. The actual practice was more a func-
29

30. tion of specific work collaborations among network members.
Networks of Networks
The concept of networks is scalable on a whole network
level to a “ network of networks” [Craven & Wellman, 1973]:
network groups connected to other network groups by actors
sharing membership in these groups. This operates in a number
of ways. People are usually members of a number of different
social networks, each based on different types of relationships
and, perhaps, different communication media. For example,
a scholar may belong to one network of researchers and also
belong to a network of friends. This person’s membership in
these two networks links the two networks: there is now a path
between researchers and the scholar’s friends.
Not only do people link groups, but groups link people; there
is a “duality of persons and groups”. The group of researchers
brings together people who are themselves members of dif-
ferent groups. Their interpersonal relations are also intergroup
relations. Such cross-cutting ties structure flows of information,
coordination and other resources and help to integrate social
systems.

31. SOCIAL NETWORK
2.1 online networks
I’ve analyzed the origin of the concept of Social Network,
its descriptive variables, and uses; but in the past ten years
this concept became a product of worldwide fame. The term
“social network” today is synonymous with online networks
like Facebook. Online communities exists since even before the
World Wide Web was invented, an early example is Usenet, a
network composed by thematic discussion groups in 1979.
In 1987 Howard Rheingold, a very active user on another
platform called “The Whole Earth Lectronic Link” (WELL),
published an early book about what he called “virtual commu-
nity”: “A virtual community is a group of people who can meet
on or off line and who share thoughts through a forum and
informatics networks.”
After that the trend became bigger: the French post lunched
Minitel, America Online was released, IBM and Sears created
Prodigy, ultimately AOL came out and absolutely dominated
the market in the States.
Common traits of all of those community was the use of a
user/nickname, this is true even for the e-mail service that
burst out in the early ‘90s.
In 1997 sixdegrees.com was the first social network with most
of the features we still use nowadays: a public or semi-public
profile page, a list of contacts, visible personal network of
friends and friends’ network, and for the first time real people’s
name, and this feature for the time was visionary. The two pos-
sible interactions were: connectMe and networkme.
But it was too early for this kind of service, both the technol-
ogy and the society weren’t ready, costs were too high and with
the boom of the dot.com the company was closed.
In 2001 the world was ready for the second round: the first
generation of social network, Plaxo, Ryze and Friendster, were
released starting from this year; and would be soon been fol-
lowed by LinkedIn, Tribe.net and MySpace.
Ryze (end 2001) was about people helping each other ‘rise up’
through quality networking, make connections and grow their
networks. You could network to grow your business, build your
career and life, find a job and make sales, as well as just keep in
touch with friends.
Plaxo (Nov.2002), funded by Sean Parker was an online address
book and social networking service integrated with Microsoft
Outlook, viral it identified in a reliable way a person based on
his friendships.
Friendster (Feb. 2003), the most successful one, was a service
that allowed users to contact other members, maintain those
contacts, and share online content and media with those con-
tacts. It was also used for dating and discovering new events,
bands, and hobbies. Users could share videos, photos, messages
and comments with other members via their profile and their
network; and this last one was the big revolution that helped
the website grow that big.
The second generation of social network is based on the divi-
sion between personal and business networks.
31

32. Tribe.net (early 2003) is a social network started in the San
Francisco bay area. Tribe is similar to social networks like
Facebook and MySpace, but allows users to create their own
personal networks with other users; forming “tribes.” Anyone
may register as a new tribe user, and may then define their im-
mediate network of friends, either by choosing from existing
members or by inviting new members to join. Each of these
users may in turn define their own network of friends.4
LinkedIn (May2003) with over 100 million users representing
over 200 countries around the world, LinkedIn is a fast-growing
professional networking site that allows members to create
business contacts, search for jobs, and find potential clients. In-
dividuals have the ability to create their own professional profile
that can be viewed by others in their network, and also view the
profiles of their own contacts5.
MySpace (August 2003) is one of the world’s largest social
networks, with about 125 million users. Originally inspired by
Friendster, MySpace quickly grew to become the world’s larg-
est social network, before being overtaken by Facebook. User
pages are highly customizable and support integration with
widgets such as Slide or YouTube. MySpace provides users with
a way to connect around content and culture. Today is the lead-
ing social entertainment destination powered by the passion of
fans. Music, movies, celebs, TV, and games made social6.
SOCIAL NETWORK
2.2 2004 the boom
Global Social Network Penetration schema 3
80%
70%
% Active Online Users
60%
50%
40%
30%
20%
10%
0%
s
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4 http://www.crunchbase.com/company/tribe
5 http://www.crunchbase.com/company/linkedin
6 http://www.crunchbase.com/company/myspace

33. “If we want to understand what motivates people to act in the way that
they do, we need to understand that people live in networks. When we
think of our customers, it’s easier to think about people in isolation, people
as independent actors. But that doesn’t exist, people live in networks and
those networks influence almost every aspect of their lives: what they do,
where they go, what brands they prefer, what products they buy”
P. Adams
This is how Paul Adams, user experience designer at Facebook,
previously at Google+, pictures our nowadays lives.
How did we get this far? The first milestone was set in 2004,
when Mark Zuckerberg together with his college roommates
and fellow computer science students Eduardo Saverin, Dustin
Moskovitz and Chris Hughes started “The Facebook
In fact Facebook, Twitter, and the new entry Google+ have
changed and now dominate the recent Social Network scene;
we are in the social network era: besides those three giants,
every day many new social networks come out from scratches.
If a year and a half ago, we might have thought that Facebook
and/or Twitter would have crushed any remaining competitors
and that would be the end of it, what’s happening is that other
social networks, such as LinkedIn and Google were able to find
unfilled niches, and we now have four different major social
networks, each with its own specialty, but with major overlaps.
The biggest point of overlap is in sharing news and other
content online. Each site provides a mechanism for sharing the
latest headlines with your friends and colleagues.
Here’s a representation of the most adopted social networks.
SOCIAL NETWORK ADAPTION CYCLE
schema 4
In the innovators area we can place Friendfeed, which stopped
innovating after its acquisition by Facebook; Foursquare, the
most famous location based social network with 10 million
users; and Google+ with its explosive adoption rate (20 million
users in 3 weeks).
In the early adoption stage we find professional social net-
works like Viadeo and LinkedIn, or generalist ones like Orkut
(owned by Google), VKontakte (leader in Russian territories),
Bebo. Badoo is the only service specifically designed for dating
purposes. MySpace, after reaching the early majority is now
struggling for conquering a niche (it fell from 225 million users
to 125 million because of several management mistakes and
Facebook’s rise).
RenRen, the most important Chinese real-name SNS, and Twit-
33

34. ter were able to successfully cross the chasm and reach the
early majority. Meanwhile QZone, China’s largest nickname net-
work built on the back of Tencent’s QQ Messenger, is entering
the late majority area.
In the laggards: Facebook, the social network that has con-
quered the masses seems determined to hit the one billion users
mark.
SOCIAL NETWORK
2.3 typology
Commonly the word typology is used improperly, as mean-
ing: a classifications of specific and characterized categories,
whereas if we go back to its Greek roots the word tupos means
fuzzy shape and logia means study; the real meaning of typology
is indeed “the study of the fuzzy shapes”. I think that in this
specific case typology is exactly what I’m about to do; because
of the quantity and common shared features of the existing
social networks, it’s very hard to properly classify them. Let’s try
to categorize the most adopted ones, following two different
logics.
schema 5
SOCIAL NETWORK COUNTRY REGISTERED USERS ADOPTION RATE
facebook U.S.A 700.000.000 75%
Qzone China 481.000.000 48%
twitter U.S.A 200.000.000 20%
ren ren China 170.000.000 17%
Vkontakte Russia 135.000.000 14%
mySpace U.S.A 125.000.000 13%
badoo U.S.A 122.000.000 12%
orkut U.S.A 120.000.000 12%
linkedIn U.S.A 100.000.000 10&
google+ U.S.A 20.000.000 2%
U.S.A 1%
foursquare 10.000.000
Geography base classification
A geography based classification can be remarkable; in fact it’s
interesting to notice that all of the major social network are
born in California, U.S.A. This is not surprising: the Silicon
Valley is worldwide known for being an incubator of technol-

35. Russia
The Netherlands 26.06m
6.30m
56%
45%
62%
42%
46%
Canada 18%
11.72m P olan d
UK J apan
54% 12.03m
19.27m 13.66m
43% 48%
44% 16%
26% 46%
40% 16%
28% 26% 8%
Germany China
155.29m
18.81m
47%
USA 47%
114.55m 53%
38%
34%
South Korea
51% 32% 10.93m
51%
23%
20% Italy
12.66m 33%
France
35
15.92m 38% 11%
57% 49%
Hong Kong
45% 36% 2.56m
28%
39%
Philippines
56%
14.43m
Mexico Spain 33%
India 60%
10.10m
12.80m 35.08m 73%
47%
52% 50% 46%
45%
63% 64%
36% Malaysia
37% 49%
11.50m Indonesia
18.93m
Brazil 54%
57%
33.49m 63%
66%
54% 41 %
52%
51%
34% Singapore
1.96m
Australia
48%
7.05 m
Global Map of Social Networking 2011 57%
50 %
schema 6 32%
48 %
27 %
Behaviour Types:
active social networkers (mil)
messagers and mailers
content sharers
joiners and creators of groups

36. ogy, innovation and creativity. But since this time the topic are
social networks it’s meaningful to keep in mind that Facebook,
Twitter and so on are an American culture based, and trying to
go more and more global they are practically exporting a model
rooted into American values, such as individualism, entrepre-
neurship, or simply freedom of speech.
The country fighting for the pool with the United States is
China. China both in terms of population and of culture has a
great potential in the social network race. Mangas and video-
games are born in Asia, in particular in China and Japan indeed.
Even if they have almost the same functionality, Chinese and
American platform are deeply different.
In fact the most important social networks in terms of number
of active members are: Facebook, Qzone, Twitter and Renren.
User Experience based classification
Another interesting classification can be adopted from B.
Wirtz’s work7 “ 4C typology of business model” which clas-
sifies business model according to how they create value. I
believe that today after the social network boom, social network
can be considered an independent business model (we can
identify its operational and output system and they way it cre-
ates value) and not just “a broad factor fundamental to the Web
2.0” as B. Wirtz stated in 2010.
Therefore we can divide them according to their mission and
the audience they’re trying to reach in:
- Content-oriented: focused on the collection, selection,
compilation and distribution of online content. Their value
proposition is to provide convenient, user-friendly online access
to various types of relevant content. Their interaction logic can
be one-to-many such as Vodafone Lab (usually are companies
divisions); as well as many-to-many such as Wikipedia, Cargoc-
ollective and slideshares.
- Commerce-orientated: focused primarily on the initiation,
negotiation, payment and delivery aspects of trade transactions;
examples are eBay, and Tao Bao
- Connection-oriented: the most popular ones nowadays, they
aim at providing the network infrastructure that enables users’
participation in online networks, either on a physical intercon-
nection level, or a virtual interconnection level. We can also
call them “generalist” social network because of the generalist
nature of their content, popular examples are Facebook, Twit-
ter, Google+.
7 Wirtz B.W., Schilke O., Ullrich S., 2010, Strategic Development of Business
Models, implications of the Web 2.0 for creating value on the internet, Long
Range Planning 43, Elsevier (pp 272 - 290)

37. 2 . A N A LY S I S
37

39. ANALYSIS
3.1 Three case studies
– hypothesis
Based on previous analyzed literature, business models can
be interpreted as narratives, as “stories that explain how the
enterprise works” (Magretta). The hypothesis of this analytical
phase, which is consistent with the narrative business model
interpretation, is firstly to test the relationship between business
logic and business narrative in the social networks context, re-
marking if the “reversed” meaning generation cycle takes place
and the potential effects of it; ultimately observing if narra-
tives generate new meanings and how those new meanings are
integrated into the business logic.
BUSINESS LOGIC BUSINESS NARRATIVE MARKET
The unit of analysis selected is composed by three generalist
social networks: Facebook, Twitter, and Google+. Those are
the most significant ones because of the richness of users and
business narrative existing, and the trend setter position they
are in today social environment.
39

40. ANALYSIS
3.1 Three case studies
– Methodology of Analysis
“The message of any media or technology is its change of scale or pace”
Marshall McLuhan
I analyzed Facebook, Twitter and Google+ longitudinally, test-
ing the interaction of business logic, business narrative, and
user narrative, and their refle ction on the platform evolution.
Firstly I analyzed each social network, year by year on the four
dimensions (BL, BN, UN, platform) to confront them paral-
leled and observe how one interact with the other, withdrawing
a longitudinal picture at the end.
In a second phase I confronted the three social networks
general pictures trying to draw communalities, possible patterns
and proves of my hypothesis
The tools used were:
- Business Logic: the building blocks visualization diagram
finalized by A. Osterwalder and Y. Pigneur1 , to understand
how changes in a part of the business model would affect the
general picture
- Narrative: I divided the analysis of the narrative in three
main fields, in order: what users say, what the market says and
what the company (social network) says, gathering both text
and visual narratives
- Honey Graph: ultimately I analyzed the effect of the busi-
ness evolution from the user perspective adapting J. H. Kietz-
mann work “ the seven functional blocks of social media”2
Other variables taken into consideration were the evolution of
number of users and revenues.
Data Collection
Textual and Visual narrative data were collected both directly
and indirectly. The main direct sources were the social networks
company page, on the social network itself and in some cases
on other social networks (Twitter has its own page on Face-
book as well)
Indirect sources examined were technology online magazine
such as Techcrunch and Mashable as well as blogs and author-
ized books. TV, web TV interviews, shows participations and
official video released by Facebook, Twitter and Google+ have
been used as references as well. (Oprah’s show is a must)
1 Osterwalder A., Pigneur Y., 2010, Business Model Generation. A handbook
for visionaries, game changers, and challengers, Wiley
2 Kietzmann J.H., Hermkens K., McCarthy I. P., Silvestre B. S., 2011, Social me-
dia? Get serious! Understanding the functional building blocks of social media,
Business Horizons, Elsevier

41. ANALYSIS
THE SEVENThe seven functional blocks of social media
3.1 FUNCTIONAL BLOCKS OF SOCIAL MEDIA
Adopted from -Adopted from (Kietzmann J.H. et al.)
(Kietzmann J.H. et al.)
schema 7
extent to which users
exchange, distribute,
and receive content.
There are two kind of
sharing: one based on
extent to which users objects of sociality extent to which
communicate with users have in common, users can form
other users in a the other one consists communiteis and
social media setting. in identifying new subcummunities
Based on frequency objects that can
and content of a mediate thier shared
conversation, interests
velocity is the rate
and direction of the
change in a conver-
sation. The rate is the
number of conversa- SHARING
tion and the direction
is the continuity/
discontinuity of the
conversation
CONVERSATION GROUPS
USER
IDENTITY
extent to which
users reveal their
real identity in a
social media
RELATIONSHIP PRESENCE setting, can be
extent to which users also related to
can be related to their location or
other users, alias mood.
they have some sort Often people tie
of association that REPUTATION di erent
leads them to share. identities to the
Depending on how context of the
users are connected, di erent social
it determines the media platforms
what-and-how of extent to which users extent to which they use
information can identify the users can know
exchange. standing of others. if other users
Variables of this are: Reputation can refer are accessible:
-number of them both to people or where they are,
-position in the their contents if status is
network, available,
-kind of sources proximity
involved
-multiplexity,
-strenght of relation-
ship
41

43. f

44. ANALYSIS
3.1 Facebook
- history
Mark Zuckerberg wrote Facemash, the predecessor to Face-
book, on October 28th 2003, while attending Harvard as a
sophomore. The site represented a Harvard University ver-
sion of Hot or Not, and according to The Harvard Crimson,
Facemash “used photos compiled from the online facebooks
of nine Houses, placing two next to each other at a time and
asking users to choose the ‘hotter’ person”
To accomplish this, Zuckerberg hacked into the protected
areas of Harvard’s computer network, and copied the houses’
private dormitory ID images. Harvard at that time did not have
a student directory with photos and basic information, and
Facemash attracted 450 visitors and 22,000 photo-views in its
first four hours online. That the initial site mirrored people’s
physical community—with their real identities—represented
the key aspects of what later became Facebook.
The site was quickly forwarded to several campus group list-
servers, but was shut down a few days later by the Harvard
administration. Zuckerberg was charged by the administration
with breach of security, violating copyrights, and violating
individual privacy, and faced expulsion. Ultimately, however, the
charges were dropped. Zuckerberg expanded on this initial pro-
ject that semester by creating a social study tool ahead of an art
history final, by uploading 500 Augustan images to a website,
with one image per page along with a comment section. He
opened the site up to his classmates, and people started sharing
their notes.
In January 2004, he began writing code for a new website; he
was inspired, he said, by an editorial in The Harvard Crimson
about the Facemash incident. On February 4th 2004, Zuck-
erberg launched “Thefacebook”, originally located at theface-
book.com.
Just six days after the site launched, three Harvard seniors,
Cameron Winklevoss, Tyler Winklevoss, and Divya Narendra,
accused Zuckerberg of intentionally misleading them into
believing he would help them build a social network called
HarvardConnection.com, while he was instead using their ideas
to build a competing product. The three complained to the
Harvard Crimson, and the newspaper began an investigation.
The three later filed a lawsuit against Zuckerberg, subsequently
settling.
Membership was initially restricted to students of Harvard
College, and within the first month, more than half the
undergraduate population at Harvard was registered on the
service. Eduardo Saverin (business aspects), Dustin Moskovitz
(programmer), Andrew McCollum (graphic artist), and Chris
Hughes soon joined Zuckerberg to help promote the website.
In March 2004, Facebook expanded to Stanford, Columbia,
and Yale. This expansion continued when it opened as well to
all other Ivy League schools and Boston University, New York
University, MIT, and gradually most universities in Canada and
the United States.
Facebook incorporated in the summer of 2004 and the entre-
preneur Sean Parker, who had been informally advising Zucker-
berg, became the company’s president.
In June 2004, Facebook moved its base of operations to Palo

45. Alto, California. Facebook received its first investment later
that month from PayPal co-founder Peter Thiel. The company
dropped The from its name after purchasing the domain name
facebook.com in 2005 for $200,000.
Facebook launched a high school version in September 2005;
but by invitation only. Later that year it expanded member-
ship eligibility to employees of several companies, including
Apple Inc. and Microsoft as well. On September 26th 2006,
Facebook opened to everyone of ages 13 and older with a valid
email address.
In October 2007, Microsoft purchased a 1.6% share of Face-
book for $240 million, giving Facebook a total implied value
of around $15 billion. Microsoft’s purchase included rights to
place international ads on Facebook.
In October 2008, Facebook announced that it was to set up its
international headquarters in Dublin, Ireland.
In September 2009, Facebook claimed that it had turned cash
flow positive for the first time. In June 2010, an online market-
place for trading private company stock reflected a valuation of
$11.5 billion.
Traffic to Facebook has increased steadily since 2009. More
people visited Facebook than Google.com for the week ending
March 13th 2010.
Facebook has also become the top social network across eight
individual markets in the region, Philippines, Australia, Indo-
nesia, Malaysia, Singapore, New Zealand, Hong Kong and
Vietnam, while other brands commanded the top positions in
certain markets, including Google-owned Orkut in India, Mixi.
jp in Japan, CyWorld in South Korea and Yahoo!’s Wretch.cc in
Taiwan.
45

46. ANALYSIS
3.2 Facebook
– 2004
Product Evolution
The following parts were implemented:
- personal profile
- wall
- universities networks
- group application
- possibility to “poke”
- wirehog work in progress
f
Business Logic
schema#
schema 8
-implement the Network
website co-creation
-deal with
server
A place to Ivy league
overloading
collect info and Stanford
-PR with
about students and
universities
ourselves to sta
be shared with
our friends,
-harvard email platform to -theface
account host user book.com
-opensource generated -personal referral
software contents -wordofmouth
-users
behaviour datas
hosting server ADV: colleges and local businesses
banner and special promotion page

47. Textual Narrative
A. Lester, The Crimson
f
“An element of wanting to belong, a dash of vanity and more
than a little voyeurism probably go a long way in explaining
most addictions (mine included). But most of all it’s about per-
forming—striking a pose, as Madonna might put it, and letting
the world know why we’re important individuals. In short, it’s
what Harvard students do best.”
“it’s a flirting tool”
“it becomes users’ agenda”
“it’s a tool to stalk people”
f
M.Zuckerberg
“I’m pretty happy with the amount of people that have been
to it so far,” he said. “The nature of the site is that each user’s
experience improves if they can get their friends to join it.”
Fb Homepage
“Fb is an online directory that connects college students
throughout social networks”
“Thefacebook is now available to all Harvard students. You
can use Thefacebook to: look for students in your major, find
out who’s attending same classes as you, look for your friends’
friends, visualise your social network”
Visual Narrative
img. 1
47

48. img. 2
schema #
GROUPS
GROUPS
CONVERSATION SHARING CONVERSATION
f f
USER IDENTITY USER IDENTITY
RELATIONSHIP RELATIONSHIP
PRESENCE
REPUTATION REPUTATION