Setting The Stage For Empirical Research In Virtual Social Networks

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Setting the Stage for Empirical Research in Virtual Social Networks

Introduction

This work sets the theoretical stage for future empirical investigations of the socio-
economic dynamics in virtual social networks (VSN), at member and network
entrepreneur levels. In so doing, I start by identifying the empirical loci, Flickr and
LinkedIn, justify and describe the choices. A model of the utility function of the generic
VSN member is followed by descriptions of the value dynamics for each VSN, which in
turn create the premise for an economic model of VSN as platforms for multi-sided
markets. The model is built by considering several theoretical angles from the
perspectives of microeconomics and sociology of networks. The contribution is in
extending theoretical and empirical insights across disciplines and fields with the idea of
exploring and understanding the emerging VSN-phenomenon.

Empirical Loci

Wikipedia defines a virtual community as “a social network of individuals who interact
through specific media, potentially crossing geographical and political boundaries in
order to pursue mutual interests or goals. One of the most pervasive types of virtual
community includes social networking services, which consist of various online
communities.1”

The empirical lens is applied to Flickr and LinkedIn, which are social networking
services, or virtual social networks (VSN) whose themes are photo-sharing and
professional networking, respectively.2 The VSN choice was made for analytical
simplicity, for these two networks are monothematic, and illustrate supply or network-
side similarities, and demand or member-side contrasts. On the supply side, these
networks are platforms for multi-sided markets, whereas on the demand side they
represent, let us say, types of utility realization. Flickr stands in for networks whose
members satisfy utility in the present; LinkedIn is a case of network whose members’
utility satisfaction is deferred. This is to say that, a) Flickr members get satisfaction at
the time of browsing, and b) LinkedIn members get deferred satisfaction, upon landing
a new job.

Before a model for the member’s utility function is advanced, we should also note that
Flickr and LinkedIn are the most prominent VSN in their niches, which is to say that
demand-side economies of scale appear to have selected each as the leader.

1
http://en.wikipedia.org/wiki/Virtual_community
2
The official description of each VSN is in Annex 1.

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Modeling the VSN Members’ Utility Function

Nature has placed mankind under the governance of two sovereign masters, pain and
pleasure. It is for them alone to point out what we ought to do, as well as to determine
what we shall do. 3

The number of members a VSN can theoretically have is the whole internet population,
for the same individual can belong to more VSN at once. In practice, all kinds of limits
are present, e.g., time, language, theme interest, etc. The two types of resources VSN
need are the technology infrastructure and membership. Holding the cost of the
infrastructure constant regardless of the membership size, for now, a VSN can be in
competition for members’ attention across different niches.4

From a microeconomics perspective, the empirical opportunity is to model and test a
network member’s utility-maximization as a function of intertemporal choices
(Nicholson et al.). If the member’s constraint is given by the amount of socializing time
on the networks (Y), the task is to find the optimal allocation between the times spent on
each network. If the choices are between spending time on Flickr (C0), and LinkedIn
(C1), then Y = C0 + C1. Taking the average time one spends on LinkedIn to get a job to be
1/r, we can say that there is deferred utility associated with C1, which is satisfied only
after an average period of time of (1/r).5 Below, there is the graphical illustration of the
utility functions Ui, associated with the intertemporal time constraint and choices,
adapted from Nicholson and Snyder (2010: 409-10).

If C1 = 0, the member chooses to spend all the time on Flickr, or C0 = Y, and there is no
time spent on LinkedIn. On the other hand, if all the time is spent on LinkedIn, C0 = 0,
and C1 = (1+r)*Y.
3
Jeremy Bentham, 1789, An Introduction to the Principles of Morals and Legislation;
http://www.econlib.org/library/Bentham/bnthPMLCover.html
4
This creates the possibility for a given VSN to extend by adopting a theme from a competitor’s niche. Facebook
appears to have embraced this path to growth.
5
To be more accurate, r should be a probability following a certain probability distribution.

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Utility maximization is achieved at (C0*, C1*), at which point the marginal rate of
substitution (MRS) between C0 and C1 is equal to (1 + r).6 It should also be observed that
r measures the opportunity cost that the member incurs when choosing to satisfy utility
at the present time rather than at some point (1/r) in the future.7

If this is a model for the utility function on the demand side, the open question now
becomes the extent to which network effects can explain the behavior of VSN after the
network reaches the dominant position. To be able to address this question, from the
supply side, next we examine the value dynamics for all network participants: members,
advertisers and entrepreneurs or owners.

Value Dynamics in Two Types of VSN

It should be noted from the outset that a way of representing structure related value-
dynamics in social networks is by virtue of structural holes. Burt defined them as
characteristic of any social structure in the following terms:

Players [network members] are connected to certain others, trusting of certain others,
obligated to support certain others, dependent on exchange with certain others. Push
here and someone over there moves. […] The holes in social structure, or, more simply,
structural holes, are disconnections or nonequivalencies between players in the arena.
Structural holes are entrepreneurial opportunities for information access, timing,
referrals, and control (1992).
Gaps between clusters [members or member communities in the network] are holes in
the structure of information flow, or more simply, structural holes. A structural hole
between two groups need not mean that people in the groups are unaware of one
another. It means only that the people are focused on their own activities such that they
do not attend to the activities of people in the other group. Holes are buffers, like an
insulator in an electric circuit. People on either side of a structural hole circulate in
different flows of information. Structural holes are the empty spaces in social structure.
The value-potential of structural holes is that they separate nonredundant sources of
information, sources that are more additive than overlapping (2005).

It follows that the members in VSN look to bridge structural holes, defined in the largest
sense of the concept, and the network itself is the broker between members or member
communities across different structural holes. A structural hole can be taken as a
fraction denoting the inverse of the strength of the relationship between two agents, or
as Burt re-frames it, the entrepreneurial opportunity and motivation (1992). In Burt’s
model, the size of the entrepreneurial opportunity is directly related to the structural

6
C0 and C1 are being assumed as modeling substitutes. This is an assumption consistent with the member’s already
having a job. Otherwise, they would be more like complements where 1 ≤ C1 and 0 ≤ C0.
7
Moreover, by changing r, we could model various utilities associated with future job changes, which reflect
substitution and income effects. If r = 0, we notice that the choice of time spent on socializing in two virtual
networks turns the model in that of maximizing utilities between simple substitutes within a budgetary constraint,
without intertemporal differentiations.

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hole, or weaker ties between agents make for better entrepreneurial opportunities. As
well, the physical network acts as broker on behalf of the network entrepreneur.

First, we look at the value dynamics of Flickr, as two-sided platform enabled by the
network entrepreneur for the member and advertiser communities, respectively.
Second, we look at the value dynamics of LinkedIn, a three-sided platform for member,
employer, and advertiser communities. At this point, it is useful to have a look at Annex
2 to learn about the main types of actions the members of Flickr and LinkedIn can
undertake.

Flickr, 2-sided value dynamics

Flickr is a web service for hosting, sharing and managing image-, and video-content,
and online community. It offers two types of accounts: Free and Pro. Free account users
are allowed to upload 300 MB of images a month and 2 videos. Also, if a free user has
more than 200 photos on the site, they will only be able to see the most recent 200 in
their photostream. Pro accounts allow users to upload an unlimited number of images
and videos every month and receive unlimited bandwidth and storage.

1.a) The network value from the perspective of the members comes through their
observable network actions: Creation, Exploration, Socialization, Negative
externalities, and Buying.

Creation: Members post photos or videos with captions. Here, the user’s objective is to
post as many photos as possible so that the Socialization objective is achieved. The
limits or costs are: time, skill, location, equipment, level of membership (paid or free),
the contribution inducing urge elicited by the results of exploration, and the amount of
social recognition garnered (Hertel et al. 2003; Davidovici-Nora 2009). The objective is
to contribute those photos that will get the most social recognition—however, some, may
even target licensing deals, or straight sales.

Exploration: Members find photos from across structural holes spanning location,
time, skill, equipment, etc. The limits here are: time to browse. Here, the user’s
objective is maximizing the finds over the search-time unit. The network entrepreneur
helps by providing random and social means to minimize costs: featured photos from
members, and the social mechanisms (homophily based exploration: the preferences of
my friends/preferred authors are more likely to become my preferences.)

Socialization: This consists of members’ commenting on photos, marking other
photos as favorite, creating, joining, and leaving groups/communities, adding one as
contact of friend—which automatically displays their latest photos on one’s homepage.
The objective here is to interact and lower exploration costs. The costs here are time,

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and emotional. The network entrepreneur creates all kinds of levels of socialization—
one may choose to keep oneself anonymous from others’ searches, or to regulate the
levels of access to one’s photos. The identity of the individuals is a matter left at the
discretion of the surfer.

Negative externalities: Members can download and use photos without, or against,
explicit permission from the author/owner. This is an activity yet unspoken of in the
context of VSN. However, it is real, and the network entrepreneur has all incentives to
discourage and downplay its incidence, for it has the potential to take the network down.
The users themselves seldom get to see their photos stolen or misused, yet it happens
every so often.8 The other type of negative activity is flaming—and this has been
documented since the early days of the online newsgroups. The solution here is on a
case-by-case basis—one can simply delete a comment, or ban another user altogether—
e.g., the White House photostream has suspended the capability of users’ commenting
on the individual photos. The lowest type of value negative externality is the presences
of free riders—users who only surf, yet don’t post either photos or comments. Given the
richness of the environment, and the low marginal cost on the part of the network
entrepreneur to serve these users, their effect is yet to be quantified. On the other hand,
they are most likely consumers of advertising, so they generate a modicum of overall
value—each photo has displayed the number of viewers and public comments; if one
subtracts from the number of visits the number of favorites and comments, one gets the
upper bound of free ridership for each photo.

The beneficiaries of all types of negative activity are those who break the written and
unwritten VSN rules. The costs for the community are born by the individual
contributors, yet considering the richness of the whole space, it must have been a
manageable quantity.

Buy: Members either buy pro-accounts, or have free membership and are advertised
to. The latter make buy decisions based on the ads they are exposed to. It should be
observed that the free members enjoy all the socializing facilities of the paying users, yet
their cost is regulated by strict limits on how many photos they can post. This means
that they are very well characterized by their social activities, e.g., a membership in a
Leica cameras group makes one a good target for sellers of Leica equipment and
accessories.

2.a) The network value from the perspective of the advertisers comes in the form of
goods and services sold, and/or increased brand awareness.

8
From the author’s +90 contacts, over 3 years, two have complained about their photos’ being stolen and/or
misused. Their solutions consisted in one case in restricting access to family photos only to those in the Friends
List, whereas the other has started watermarking his photos. It should be mentioned that these are two of the highest
contributors, in terms of number of photos and/or quality, in the author’s Contacts List.

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Advertisers benefit from being able to target very well segmented audiences. The
socializing activities of the network members should characterize very well the
audiences, that is, the network members.

3.a) The value dynamics perspective of the network entrepreneur is realized in terms
of advertising revenue, and paid membership.

The Flickr network entrepreneur is Yahoo as owner and operator of the physical
network. From the structural holes perspective of VSN, Fickr is the platform brokering
across structural holes between users, and/or users and advertisers. Flickr’s economic
model is subjected to scale economies and diseconomies. Its objective is to generate
revenue, from paid membership and brokerage fees from advertisers, at a marginal rate
above or equal to the marginal cost of operating the network.

The objectives for the network entrepreneur are: 1) to span as many and wide structural
holes as possible, 2) to qualify very well the users in terms actionable by the advertisers,
3) to reduce negative externalities, especially through the members’ own actions or
automated mechanisms. For example, Flickr reduces the effects of the free riders by
suspending memberships inactive for 90 days. In other words, the value for them is in
qualifying audiences for advertisers.

LinkedIn, 3-sided value dynamics

Applying for jobs online has been a game changer. The candidates’ cost of applying for a
job decreased to the time it takes to submit a resume and fill in an online form. The
employers’ cost of processing the job applications grew as candidates could broadcast
their resumes to many more employers than before. Moreover, the risk of mismatch
due to noisy signaling or depreciated information processing capacity grew rapidly once
job applications moved online. LinkedIn, a platform for managing professional profiles
and matching job applicants with employers, has gone into addressing the shortcomings
of the online job application process.

LinkedIn is a web service for hosting professional profiles and member communities. It
offers two types of accounts: Free and Premium, and the employers are charged for
posting jobs. Free account users are allowed limited capabilities in comparison to
premium accounts that allow members, for example, to connect and contact directly
with any other network member. In addition, those members who post jobs, employers
or recruiters, have to pay for each posting.

1.b) The network value from the perspective of the job-seekers comes through their
observable network actions: Profile creation and management, Re-Socialization,
Learning, and Buying.

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Profile creation and management: The job seeker, current or future, is creating a
profile that is much richer in content and specifications than the regular job application.
In addition to the information contained by the regular resume, the job applicant can
add several other dimensions to her professional profile. These are usually reflections of
the candidate’ prior socializing, in real life or on LinkedIn, and are likely to provide the
potential employer with a much richer signal than the resume alone. The objective of
the candidate is to build an image of a professional who is well respected for her
technical and individual qualities. In other words, the job seeker wants to signal
professional competence and personal integrity, or that the job seeker has social and
intellectual capital vetted by the members of some professional community, even if only
virtual. The limit here is imposed by the amount of socialization.

Re-socialization: This consists of getting endorsements and recommendations from
the larger community of professionals in a group, or from colleagues and supervisors in
past and current positions. Additionally, people are active in the professional
specialized communities in LinkedIn with the idea of generating new business
opportunities, learning, or simply having fun while investing in long term payout
relationships. The job seeker is socializing or re-socializing to increase her social and
professional recognition and learn about job opportunities from professionals other
than the recruiting managers who add an extra processing step to the whole application
—thus increasing the chance for signal misjudgment. The limit here is the knowledge
and time of the job seeker. Making a fool of oneself can backfire, or getting too many
low quality endorsements (e.g., from people in low positions) can also be detrimental.
So, a job seeker ought to be careful in how she allocates her time and intellectual capital
on socializing activities.

Also, when socializing in a professional group that is not necessarily prompted by a job
application, the job seeker is likely to reveal more facets of her personality; good
candidates would want to come across as they are, and employers are likely to seek out
such information. The many ways in which job seekers are building social and
intellectual capital are subject to inputs and feedback with increased variety and
objectivity—or at least, the outside observer can assess the objectivity and variety of
links and endorsements.

Learning domain knowledge and job/business opportunities: These are the
effects of the members’ actions, which can be also expressed in term of investments in
intellectual and social types of capital. This is an ongoing type of exploratory activity
whereby the job seeker learns new professional insights as well as opportunities. This is
construed in terms of a diffused benefit, knowledge building, and a potential benefit of
finding about and applying to a job opportunity before others. The clear limitation here
is the time required to scan the environment since the payouts are deferred and random,
respectively. Another cost here is the type of account a job seeker has. Professional

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accounts offer job seekers higher levels of direct access to other network members. Free
account job seekers do not have these abilities, which automatically restricts the scope of
their search, in addition to adding the cost of taking advertising.

2.b) The value dynamics perspective of the employer is about sourcing for applications
for job openings and environment scanning.

Sourcing for applications: Employers, or recruiters, need to fill the open positions
with qualified candidates who match the functional requirements. Their objective is to
reduce the processing time by being able to filter out mismatches, on any one dimension
of a job seeker application. For example, a recruiter can automatically disqualify
applications of those job seekers who do not have at least three recommendations from
supervisors. Once several automatic filtering criteria are employed and the pool of
candidates is reduced to a manageable size, the recruiter can go on with a process of
manual sorting of the remaining applications. The limitation here is the reliability of the
socialization process on the job-seeker side, yet the recruiter can always find out
additional triangulation heuristics. There is also a cost incurred by posting a job
opening with LinkedIn.

We should observe at this time that the value perspectives of the LinkedIn-advertisers,
and -entrepreneur are identical, in general terms, to those on Flickr, respectively. The
implication of this observation is that the analytical models of the two kinds of networks
are more or less identical when describing the economic model of the entrepreneur. In
effect, as suggested by the structural holes theory, the entrepreneur creates a platform to
enable autonomous interactions between network members across structural holes. It
so happens that the members’ value dynamic in each type of network, i.e. present of
future satisfaction of utility, segments the membership in groups that not only the
members themselves, but also advertisers and recruiters find valuable. In conclusion, so
far we have created several empirical opportunities and laid the premise for a unified
economic model of the network entrepreneur.

An Economic Model of the Network Entrepreneur: Multi-sided Markets

The network effect, or demand-side economies of scale, goes back in time to the early
days of telephony and has stipulated ever since that the value of a network grows much
faster than the linear progression of adding a new member.9 Prompted among others by
the hardware-software markets, Katz and Shapiro revived the classic network effect
story and showed that demand-side economies of scale cause growth in an existing stock
of consumer utility as new consumers join in the consumption of given goods (1985).

9
There is an assertion, known as Metcalf’s Law, suggesting that the value of a network with N members is N2.
Source: http://en.wikipedia.org/wiki/Metcalfe's_law

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With the advent of the internet, the network effect has become a prominent feature of
the new medium reflected in many an academic work about the value of the virtual
networks enabled by the internet.

A special case of network effects is the so-called multi-sided network or market, in
which an increase in one kind of membership increases the value of a complementary
product to another distinct kind of membership—this being a reflexive relation. Rochet
and Tirole are among the first to have studied two-sided markets by looking at the credit
card two-sided network of buyers and sellers and showing that an optimal pricing
strategy subsidizes one side of the market, as in increased adoption and growth in use by
buyers, by increased revenue from the other side of the market, as in sellers accepting
credit card payments (2003). The strategic tradeoff is which side of the network to
subsidize. The following figure, adapted from Wikipedia, illustrates the contrast
between charging each side of the platform vs. subsidizing on side of it with increased
revenue from the other side.10

Flickr and LinkedIn, by subsidizing the more price sensitive side of the network whose
size increases as result, i.e., photo-enthusiasts, job-seekers, can generate more revenue
from the advertisers, and advertisers and/or recruiters, respectively. That is illustrated
in the above figure by comparing the blue box, which is lost revenue from regular
network members, to the red box, which is the increased revenue from advertisers and
recruiters. The condition here is for the red area on the right side figure to be greater
than the light-blue area on the left side figure. Moreover, this has been shown to
increase indeed the network size (Parker et al. 2005).

A second insight yielded by the analysis of two-sided networks is that the entrepreneur
ought to subsidize the side that adds network value. Parker and Van Alstyne show that
“at a high level of externality benefit, the market that contributes more to demand for its
complement is the market to provide with a free good” (2005).11 The following figure,
adapted from Wikipedia, illustrates this insight.
10
http://en.wikipedia.org/wiki/Two-sided_market

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It is therefore that network members add value to Flickr and LinkedIn, so they get to be
subsidized. The explicitly higher value for the paying side in the network is precisely the
result of the autonomous segmentation network members do.

In conclusion, VSN such as Flickr and LinkedIn enjoy the economies of multi-sided
platforms (Rochet et al. 2003). These are coordinators of demands from various types
of customers.

Discussion and Future Research

We have seen that VSN, an emerging socio-economic phenomenon, can be well
characterized in microeconomics, and micro–social terms in order arrive at an overall
network economic model starting from individuals’ behaviors. For example, in the case
of Flickr, photography enthusiasts seek each other continuously through the tools made
available by the platform, e.g., posting photos, commenting on others’ photos, creating
or joining groups dedicated to particular topics, etc. The matching process between
users, or between users and objects of interest in the network, allows the network
entrepreneur to qualify the network population in segments that may be relevant for
each other, and/or for advertisers. The theory of multi-sided platforms shows that the
network entrepreneur is better off subsidizing one side of the platform (i.e. network
members) to grow the size of the network and its value for the other side of the platform.
The entrepreneur is thus able to generate more revenue from the other side (i.e.
advertisers) due to an overall larger and better-segmented network.

11
They also show that “At lower levels, firms may charge positive prices in both markets but keep one price
artificially low” (ibid.).

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Future research

In order to empirically test the above theoretically driven statements, we can think of
deploying software agents, designed specifically for the Flickr and LinkedIn’s
application programming interfaces (APIs), with the idea of collecting network data
showing the actual behavior of the members. As far as the methodology goes, there
could be two directions. The first one is the more traditional one relying on inferential
statistics. The second one, which I will sketch next, considers VSN as complex adaptive
systems, and could yield insights about the organizational structure and its evolution. I
should say that the microeconomics insights should be the first candidates for
exampling the individual behavior of network members, and if successful such
enterprise can extend the usefulness of the complex systems paradigm beyond its
currently metaphorical position.

To think of a mechanism accounting for the evolution of mature VSN, I should observe
that they are open systems, characterized by simple structures relative to their size, and
consist of large numbers of agents, connected into subsystems, and potentially
interconnectable at multi-level and in any combination possible. In the view of
organization theory, such structure is complex and characterized by hard to predict
behavior, due to its nonlinearity associated with feedback loops (Anderson 1999). In
conclusion, successful VSN appear to behave like complex adaptive systems (CAS) in
that they self-organize while continuing to import energy. In reviewing the literature on
complexity and organizations, Anderson indicates that CAS“-models represent a
genuinely new way of simplifying the complex. They are characterized by four key
elements: agents with schemata, self-organizing networks sustained by importing
energy, coevolution to the edge of chaos, and system evolution based on recombination,”
(Anderson 1999).12

The agents with schemata are the network members, and the energy importation
mechanism can be explained in microeconomics and micro-social terms. The potential
for contribution would be to go beyond static models of economics into showing the
evolution of VSN in time.

12
Anderson also makes the point that CAS informed models help organization science by “merging empirical
observation with computational agent-based simulation.” As there has been scant empirical evidence of actual
complex adaptive systems, framing virtual social networks in CAS terms should encourage more realistic
experimentation and simulation. It should also be noted that the author also indicates that the “CAS perspective
opens up exploration into how ideas, initiatives, and interpretations form an internal ecology within an
organization,” (ibid. p. 221).

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BIBLIOGRAPHY

Anderson, P. (1999). "Complexity Theory and Organization Science." Organization Science 10(3):
216-232.
Burt, R. S. (1992). Structural Holes: The Social Structure of Competition, Harvard University Press.
Burt, R. S. (2005). Brokerage and Closure. New York, Oxford University press.
Davidovici-Nora, M. (2009). "The Dynamics of Co-creation in the Video Game Industry: The Case of
World of Warcraft." Communications and Strategies(73): 43-66.
Hertel, G., S. Niedner and S. Herrmann (2003). "Motivation of software developers in Open Source
projects: an Internet-based survey of contributors to the Linux kernel." Research Policy 32(7):
1159-1177.
Katz, M. L. and C. Shapiro (1985). "Network Externalities, Competition, and Compatibility." The American
Economic Review 75(3): 424-440.
Nicholson, W. and C. Snyder Intermediate Microeconomis and Its Applications, South-Western Cengage
Learning.
Parker, G. G. and M. W. Van Alstyne (2005). "Two-sided network effects: A theory of information
product design." Management Science 51(10): 1494-1504.
Rochet, J.-C. and J. Tirole (2003). "Platform Competition in Two-Sided Markets." Journal of the European
Economic Association 1(4): 990-1029.

Annex 1: VSN Descriptions

Flickr LinkedIn

“Flickr - almost certainly the best online photo “Your professional network of trusted contacts gives
management and sharing application in the world - you an advantage in your career, and is one of your
has two main goals: most valuable assets. LinkedIn exists to help you
make better use of your professional network and
1. We want to help people make their photos help the people you trust in return. Our mission is to
available to the people who matter to them. connect the world’s professionals to make them
more productive and successful. We believe that in
2. We want to enable new ways of organizing
a global connected economy, your success as a
photos and video.”13
professional and your competitiveness as a company
depends upon faster access to insight and resources
you can trust.“14

Annex 2: VSN Members Actions

Flickr LinkedIn

Join the overall network at no-charge or Join the overall network at no-charge or

13
http://www.flickr.com/about/
14
http://press.linkedin.com/about

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premium level premium level

Social Join a group Join a group

Create a group (open or with rules) Create a group (open or with rules)

Connect with a member Connect with a member

Mark a member as a friend Mark a member as a colleague

Post a comment/mark as favorite Post a question/reply

Add a member to your network Add a member to your network

Write/accept a reference about/from a Write/accept/request a reference about/from a
connection connection

Communicate with a member Communicate with a connection

Undo any of the above Undo any of the above

Recommend a photo to a connection Introduce a connection to a job

Control Manage presence levels Manage presence levels

Report abuse/flag inappropriate Report abuse/flag inappropriate

Thematic Browse/search photos Browse/search job postings

Browse/search members Browse/search members

Post a photo Post a resume/job

Download a photo Apply for a job

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Setting The Stage For Empirical Research In Virtual Social Networks

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