richer visualizations of social network ties
social network visualizations do not typically focus on the nature
of relations or ties between individuals; thus, a single directional
edge is often used to connect two person nodes. This edge does not
represent the strength of the relation, or its nature. Are these
two people co-workers, activity buddies, lovers? Is the relation
recriprocal or one sided? To be fair to those researchers who devised
these visualizations, the data given to them is probably representative
of one only relation. Even if the data allowed for multiple relations
to be known, it would probably be confusing to encode and display
multiple relations, particularly in a large network; whereas a keep-it-simple
approach could eschew the uninterpretability of the visualization.
However, if we were to visualize the multiplexity of social ties,
important patterns might emerge.
"Studying Online Social Networks," Garton et
al. positions the deconstruction of social ties into bundles
of disparate, directional relations as being key to understanding
how individuals cluster in social networks, how these clusters overlap,
and how clusters endure or fall apart. A key concept is the simplexity
versus multiplexity of social ties. If a social tie features many
different types of relations (e.g. co-workers, one tutors the other,
watch baseball together), and if many of these relations are mutual,
then the tie is known as a multiplex tie, and can be seen as durable.
The durability of a single tie can impact the larger social network;
for example, if a particular person is at a cut-point point
and a tie is broken, a large subset of the network may drop out.
It is also understood that individuals who are capable of relations
not possessed by other members of his/her group or organization
may serve the all important social role of gatekeeper.
aforementioned reasons make a compelling case for the inclusion
of the simplexity/multiplexity of ties in social network visualizations.
In the following sketch, we propose a way of including information
about multiplexity into social networks, being sensitive not to
overload the network visually.
1. Social network visualization, with emphasis on multiplex
cut-points, group stability, the potentiality of ties, and gate-keepers.
represent individuals, colors code for the possession of certain
social currencies, which may be of a general nature such as physical
desirability and intelligence, or of a specific nature such as devotion
to a church, devotion to work, devotion to a hobby, membership in
a class, etc. The thickness of ties between individuals are indicative
of the multiplicity of relations shared, not the scalar magnitude
of a single shared relation. We can analyze the utility of such
a visualization as follows. The more colors possessed by an individual,
the bigger is his/her capacity to form multiplex relations. Because
the boldness of lines represents multiplexity and not magnitude,
not only can we identify groups but we can comment on the
stability of these groups. The color coding also helps
us identify the gatekeepers in a group. For example, suppose the
red squares represented individuals in a church, and the lime squares
represented individuals in politics. We can see that the red-lime
squares and the rainbow squares are the gatekeepers who control
the flow of information/influence from politics to the church, and
vice versa. Cut-points can also be identified. For example, in the
center of the sketch, a red/lime square is weakly tied to a teal/lime
square. This is a potential cut-point because even at their maximum
potential for ties, they can only be weakly linked, having only
one compatible color. Contrast this to the red-lime square weakly
connected to the rainbow square at the bottom-middle. Although this
is a weak link, there is more potential for the link to be strong,
so there is hope that this is not in danger of becoming a cut-point.
the above visualization, we do not consider asymmetrical relations,
unreciprocated relations. However, we note that unreciprocated relations
are unstable. There must be some social currency exchanged. If for
example, "John admires Mary, but Mary hates John," then
the relation is rather doomed. In an animation of the above visualization,
we might illustrate unreciprocated relations are pulsating between
existing and not existing. If there is already a multiplex tie and
only one relation is pulsating, it would hardly be visible. However,
consider that the above visualization was an egocentric display
of one's own social network. If a simplex tie is pulsating and it
happened to occur at a cut-point, we can imagine an entire chunk
of one's social network pulsating in and out, thus illustrating
economics metaphor for social support
"Network Capital in a Multi-Level World," Wellman
and Frank make the point that whereas in yesteryear social support
was thought of in terms of personal membership in solidary groups
such as a family, a church, and a career, today's networked world
shifts emphasis from solidary groups to individual ties. It seems
as if solidary groups give support for free. So it comes as no surprise
that living in a day and age when nothing-is-free, and no cultural,
moral, or civic duty compells us to freely support those in our
group, the amount of social support we receive is now more a function
of small-scale exchange of social capital. Wellman and Frank speak
of three factors affecting social support: the characteristics of
the individual, the nature of our ties, and responsibility of group
membership. In declaring that our day and age is one of networked
individualism, Wellman and Frank are really conceding the eroding
role of group membership in social support. We don't really feel
a duty, or possess an altruism to the group. We expect to only give
what we get from the group. This thrusts the group into a tragedy
of the commons deadlock, where members are not willing to give unless
they've gotten, so there is a stalemate. There are, however, exceptions.
The family, or at least, the nuclear family, is still intact in
western societies. So are community churches (where duty is bound
by fear of damnation!! how's that for altruism??).
the decline of group influence, social support becomes more heavily
a factor of the individual and of his/her ties. The characteristics
of the individual can be thought of as the potential of
a person to receive and give support. The nature of a person's ties
can be thought of as the realized pool of resources for
support. Just as Wellman and Frank talk about networks in terms
of capital, economics is a good all-around metaphor for
social support. I would suggest that it can even be measured that
economics is the metaphor they actually use for social support.
Taking this purely economics position of social support, I propose
the following reworking of Wellman and Frank's analytical model.
sketch: Here is a rudimentary proposal and written sketch.
Think of social supports as services you can purchase. Think of
your immediate social network as vendors, each of whom carries a
different offering of social support services (e.g. romantic, friendship,
business). You yourself are a vendor of services, and the services
you can offer and their costs are a function of the character
of your individual. You have an account with each of them with
a certain balance. If you sell them a service, money is put into
your account with them. The more business you do with one another,
perhaps the lower the cost of each service (we are more cheerful
to support a good friend), and the higher the line of borrowing
credit (we are willing to pull huge favors for someone given we
trust they are capable of reciprocating). How services are priced
is up to the individual. Other factors also come into play. For
example, a particular vendor (person) may be very popular with other
customers (their friends), and thus, their supply is lowered. Of
course, when they have less inventory, that inventory costs more.
This explains how getting a support favor from a very in-demand
friend "means" more. It may either cost you a lot of social
capital if that person is not fond of you, or not cost much at all
(if that person gives you the wholesale price on the service since
you are such a good customer).
the above sketch, we can make some nice predictions. If you are
the needy type of person, you will spend more at your vendors they
you probably have credit for, and very quickly, you will lose friends.
If you are very busy and your attention is fragmented, you have
a very low account balance with a lot of vendors, but not enough
balance to purchase anything from anyone. If you are very busy but
you give slightly more attention to a few people, these people will
pay you more for your services, in recognition of their scarcity
and thus, you will have a good account balance with these vendors.
Finally, no one likes to shop at a vendor with a bad selection,
so people are more likely to want to do business with you if you
have a lot to offer in different departments. Similarly, no one
shops at a place where supply is too low, or prices are too high.
To increase supply, keep fewer friends. To lower prices mutually,
do more mutual business. Just as in economics, I believe there is
a sweet spot where social support's supply and demand meet.
So perhaps given a person's needs and their friends, it is possible
to calculate just how much business should be done with each person.
ties as social glue
to find uniform ways to characterize a social group at a small scale
and at a large scale is somewhat akin to trying to reconcile quantum
mechanics with cosmology. At the small group level, it is an individual's
strong ties with other individuals which characterize the group.
This is perhaps what Wellman and Frank suggest with the phrase,
networked individualism. However, in looking at large groups,
weak ties exert a much stronger influence, as suggested by Granovetter.
For example, we tend to think that because we select all our friends
by choice, we must also transitively reason that our friends select
their friends by choice, and so on. That means our friends-of-friends
network should have a fantastically wide range. However, as Newman
shows in "Ego-centered networks and the ripple effect,"
these extended networks are smaller than expected. Why?
does not directly answer this question, only suggesting that it
is a mathematical characteristic of the network structure. He exhibits
mathematical formulae to calculate the range of a person's friends-of-friends
network by factoring in overlap between different circles of friends.
Granovetter's account of weak ties offers a perfect explanation.
The reason why there is overlap, is because our seemingly
100% free-willed choices of friends is actually subtly influenced
by a preference for weak, but common characteristics. These characteristics
are not so dominating as to make us feel we can't just pick whoever
we want and work at the friendship. But consider a friend of a friend.
You cannot explicitly pick that person to be a friend of a friend.
However, the same weak tie that enabled your relationship with your
friend can influence the choice of friend of a friend.
Hence, strong ties only influence your immediate friends, but weak
ties can travel many links away from you.
it is the commonality of these weak ties that creates the overlap
of friends and accounts for the narrower than expected range of
your friends-of-friends network. The influence of weak ties does
diminish as the number of friend-of-a-friend links are included
into a circle. Because the tie is "weak," it is still
plausible that a friend of a friend will completely escape the social
group you belong to, and hence, you've connected to a whole new
group where a different set of weak ties are at play.