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KIN, FRIENDS, and COMMUNITY
Anthropologists were among the earliest developers of social
network ideas to study kinship patterns of pre-industrial societies
and small rural communities. Moreno, of course, invented
sociograms to map children‟s friendship patterns. And many
sociological network analysts studied interpersonal ties within
large modern communities. The ethnographic research tradition
remains a robust contributor to social network analysis today.
Siegfried F. Nadel argued that the role system
of a society forms the matrix of its social
structure: “We arrive at the structure of a
society through abstracting from the concrete
population and its behaviour the pattern or
network (or „system‟) of relationships obtaining
„between actors in their capacity of playing
roles relative to one another‟.” (Nadel 1957:12)
Kinship Networks
Network approaches to kinship examine the structure of marriage
rules and the strategies for social bonding across generations.
Kinship involves complex interlocked role
relations, prescribing expected rights & duties
of the actors occupying distinct positions
- Sexual relations & reproduction rights
- Child-rearing obligations
- Dowries, land & property inheritance
- Cohesion/solidarity & collective action
In Anatomy of Kinship (1963) Harrison White used matrix algebra to simplify complex classificatory rules regarding marriage and parentage. These rules generate clans among people in the same kinship situation. The resulting classificatory kinship system operates as an abstract group. White showed how to classify existing clan systems into a few basic types, revealing a wider variety of clan systems than anthropologists had previously hypothesized.
Friendship on Frat Row
Theodore Newcomb (1953) started a fraternity at Bennington College
in the 1930s. In return for free room and board, 17 fratmen filled out
weekly sociometric rankings. These 15 NEWFRAT matrices, stored in
UCINET, are a classic dataset on the evolution of friendship choices.
The usual story about Newcomb‟s fraternity is
that structural convergence occurred as those
transferring college students met and formed
friendships. That interpretation comes from
network summary measures, or aggregated
blockmodels, indicating that structural change
operates through structurally equivalent actors.
However, convergence remains a controversial conclusion, because as
much as one-fifth of the friendship ties changed during in the final weeks.
Moody et al. (2004) use network “movies” to argue that “the overall
structure does not converge on a single form, and that the process of
change is heterogeneous with some actors forming stable relations while
others dance between friends throughout the observation period.”
An Evolving Network
“Two groups follow a simple convergence story -- with their nominations getting progressively more stable as time passes. The first of these groups … has 7 members, including the cluster at the right of the movie (1,6,13,8) and presents a gradual convergence of nomination patterns, while the second (with 6 members) does not converge on stable nomination patterns until week 5. Finally, group 3 (with 4 members, including hanger-on nodes 10 & 15) never seems to settle on a particular nomination pattern, but changes nominations steadily over the observation period.”
Name Generators
Instruments that measure ego-centric networks in community or national
surveys must use an open-ended “name generator” rather than an
enumerated checklist. The 1985, 1987 & 2004 GSS quex: “From time to
time, most people discuss important matters with other people. Looking
back over the last six months, who are the people with whom you
discussed matters important to you. Just tell me their names or initials.”
For each pair of alters: “Are (Name) and (Name) total strangers? Especially close?” After asking about every alter‟s gender, race, age, occupation, etc.: “Here is a list of some of the ways in which people are connected to each other. Some people can be connected to you in more than one way. For example, a man could be your brother and he may belong to your church and be your lawyer. When I read you a name, please tell me all the ways that person is
connected to you.” →→
Spouse, parent, sibling, child, other family, coworker, member of group to which you belong, neighbor, friend, professional advisor or consultant, other
Just the Facts, Ma’m
The 1985 GSS module uncovered many factoids about the social
composition of adult Americans‟ egocentric discussion networks
Median size = 3 alters; 25% have 0-1 alters, 25% have 5- Half of alters are ego‟s kin; only 20% have no kin in their networks Alters know one another: mean density = 0.61; only 5% all strangers High race/ethnic homogeneity; only 8% have any alter diversity Substantial sex diversity: 78% have at least one alter of opposite sex (most often a spouse, sibling, or parent)
“The GSS survey network data describe relatively small, kin-centered, dense, homogeneous social environments surrounding Americans. … To the extent that success of „networking‟ as an instrumentally oriented pursuit depends on access to diverse others, those best situated to make use of it are the young and middle-aged, the well-educated, and those living in larger places” (Marsden 1987:130). The 2004 GSS survey found significantly smaller ego-nets & more isolates.
Clientalistic Cultures
Clientalistic systems are prevalent in Mediterranean, Asian, and
Latin American cultures having heavily collectivist conceptions
of social organization, such as Catholic or Confucian ethics.
“Patron-client systems combine strong emotional,
particularistic ties with simultaneous but unequal
exchanges of different types of resources. …
Clients exchange personal loyalty, deference, and
awe for the protection, understanding, and
material benefits provided by their patrons.”
(Knoke 1990:142).
Most cliques and entourages surrounding a patron are modeled
after patriarchal clans and extended families. Kinship forms the
inner hub, grounded in familial intimacy and trust. The spokes
are friends and acquaintances who perform brokerage services,
manipulating others‟ resources for their own profit. The result is a
hierarchical status structure connecting higher and lower strata.
Fischer, Claude. 1982. To Dwell Among Friends: Personal Networks in Town and City. Berkeley, CA: University of California Press.
Knoke, David. 1990. Political Networks. New York: Cambridge University Press.
Marsden, Peter V. 1987. “Core Discussion Networks of Americans.” American Sociological Review 52:122-131.
Moody, James, Daniel McFarland, Skye Bender-de Moll. 2004. “Dynamic Network Visualization: Methods for Meaning with Longitudinal Network Movies.” (Downloaded October 2, 2004) <www.sociology.ohio-state.edu/jwm/NetMovies/Sub_CD/dynamic_nets_public.html>
Nadel, S. F. 1957. The Theory of Social Structure. London: Cohen & West.
Wellman, Barry. 1979. “The Community Question: The Intimate Networks of East Yorkers.” American Journal of Sociology 84:1201-1231.
White, Douglas R., Vladimir Batagelj and Andrej Mrvar 1999. “Anthropology: Analyzing Large Kinship and Marriage Networks with Pgraph and Pajek.” Social Science Computer Review 17(3):245-274.
White, Harrison C. 1963. An Anatomy of Kinship: Mathematical Models for Structures of Cumulated Roles. Englewood Cliffs, NJ: Prentice-Hall.
Yi, Lee Mei and Paul Ellis. 2000. “Insider-Outsider Perspectives of Guanxi.” Business Horizons 43:25-30.
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