CONNECTIONS - INSNA

CONNECTIONS
Configurations of Homophily
Finally, inbreeding homophily can emerge
because individuals prefer to associate with
similar others (Skvoretz, 1983). Possible
sources for this preference include
communication facilitation (Rogers &
Bhowmik, 1970), impressions of cognitive
compatibility (Huston & Levinger, 1978), and
energy efficiency (Mayhew et al., 1995).
Preference homophily can be conceptualized as
the residual homophily that exists beyond that
explained by baseline levels, consolidation, and
substructural foci.
The present research focuses on homophily
produced through substructures and individual
preference. Baseline homophily and inbreeding
homophily due to consolidation at the
population level are controlled.
Multidimensionality
Several researchers have recognized the
multidimensional nature of homophily in
relations, i.e., that individuals are simultaneously
drawn together or repelled from one another
based upon a range of characteristics (Blau,
1977; Burt, 1990; Huckfeldt, 1983; Laumann,
1973; Popielarz & McPherson, 1995; Rogers &
Bhowmik, 1970; Skvoretz, 1983). Early
research on homophily primarily examined a
single dimension (Feld, 1982; Hallinan &
Williams, 1989; Robins, Elliott & Pattison,
2001) or multiple dimensions in sequence (Blau
et al., 1984; Burt, 1990; McPherson & Smith-
Lovin, 1987; Marsden, 1987; Skvoretz, 1990).
Such research detailed the gradations of
homophily, the relationship between social
position and homophily, and how, independent
of one another, some dimensions are more
salient and exert a stronger influence on
association than others (Marsden, 1987, 1988).
Recently, statistical models have emerged as a
means to examine homophily on multiple
dimensions simultaneously. Two examples are
the stochastic actor-oriented model (Snijders,
Steglich, & van de Bunt, 2010) and exponential
random graph models (Robins, et al., 2007;
Wasserman & Pattison. 1996). Using such
approaches, researchers have continued to find
evidence for homophily on individual attributes,
including race/ethnicity, sex, and age
(Goodreau, Kitts, & Morris, 2009; Mouw &
Entwisle, 2006; Schaefer, Light, Fabes, Hanish,
& Martin, 2010). While such research considers
multiple dimensions simultaneously, thereby
controlling for consolidation, models typically
do not include interactions between dimensions.
This implicitly assumes that interactions
between homophily dimensions are independent
or unimportant. The current research relaxes the
assumption of independent dimensions and
explores how dimensions operate in conjunction
to influence the likelihood of association.
The current research aims to identify which
combinations of homophily occur more often
than expected by chance. I present a settheoretic
approach to the patterning of
homophily across several dimensions. I eschew
measurement complexity in order to gain an
understanding of the broader patterns of
homophily across multiple dimensions. Given
the limited research that has considered
homophily multidimenionally, this approach
serves as a useful starting point.
Configurations of Homophily
This research defines homophily as a “crisp set”
(individuals are either similar or dissimilar) and
relations are either in the set of “homophilous
relations” or outside the set. To measure
homophily for any pair of individuals, I measure
their individual scores on a dimension and then
classify their similarity. For a condition x,
relations in the “x homophily” set are similar on
dimension x, while those outside the set are
different on x. For example, relations between
individuals who are the same age are members
of the set “age homophily” and those between
individuals of different ages are outside of the
set “age homophily.”
The multidimensionality of homophily is
measured by classifying relations as
configurations of homophily. A configuration of
homophily is the pattern of similarity across a
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