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Social Isolation in America: Changes in Core
Discussion Networks over Two Decades

Miller McPherson

University of Arizona and Duke University

Lynn Smith-Lovin

Duke University

Matthew E. Brashears

University of Arizona

Have the core discussion networks of Americans changed in the past two decades? In
1985, the General Social Survey (GSS) collected the first nationally representative data
on the confidants with whom Americans discuss important matters. In the 2004 GSS the
authors replicated those questions to assess social change in core network structures.
Discussion networks are smaller in 2004 than in 1985. The number of people saying
there is no one with whom they discuss important matters nearly tripled. The mean
network size decreases by about a third (one confidant), from 2.94 in 1985 to 2.08 in
2004. The modal respondent now reports having no confidant; the modal respondent in
1985 had three confidants. Both kin and non-kin confidants were lost in the past two
decades, but the greater decrease of non-kin ties leads to more confidant networks
centered on spouses and parents, with fewer contacts through voluntary associations and
neighborhoods. Most people have densely interconnected confidants similar to them.
Some changes reflect the changing demographics of the U.S. population. Educational
heterogeneity of social ties has decreased, racial heterogeneity has increased. The data
may overestimate the number of social isolates, but these shrinking networks reflect an
important social change in America

There are some things that we discuss only
with people who are very close to us. These
important topics may vary with the situation or
the person — we may ask for help, probe for
information, or just use the person as a sound-
ing board for important decisions — but these are
the people who make up our core network of
confidants. How have these discussion networks
of close confidants changed over the past two

decades? We address that question here with
data from a high-quality national probability
survey that collected parallel data in 1985 and
2004. We find a remarkable drop in the size of
core discussion networks, with a shift away
from ties formed in neighborhood and com-
munity contexts and toward conversations with
close kin (especially spouses). Many more peo-
ple talk to no one about matters they consider

Please address correspondence to Miller Networks in Columbus, Ohio, and at the Social

354 AMERICAN SOCIOLOGICAL REVIEW

important to them in 2004 than was the case two
decades ago.

Why is this question (and its disturbing
answer) significant? Social scientists know that
contacts with other people are important in both
instrumental and socio-emotional domains
(Fischer 1982; Lin 2001). The closer and
stronger our tie with someone, the broader the
scope of their support for us (Wellman and
Wortley 1990) and the greater the likelihood that
they will provide major help in a crisis (Hurlbert,
Haines, and Beggs 2000). These are important
people in our lives. They influence us directly
through their interactions with us and indirect-
ly by shaping the kinds of people we become
(Smith-Lovin and McPherson 1993).

Much of what we know about these core con-
fidants comes from surveys that measure ego-
centered networks — relationships from the point
of view of a single person. These data describe
the interpersonal environment of an individual.
They allow us to measure the degree to which
that person is directly connected to different
parts of a social system and integrated into it at
the individual level.

Building on earlier network surveys (e.g.,
Fischer 1982; Verbrugge 1977; Wellman 1979),
the General Social Survey (GSS) measured the
national U.S. social system of ego-networks for
the first time in 1985 (Burt 1984; Marsden
1987). Since then, our description of the core
interpersonal environment for Americans has
been frozen in the mid-1980s. Of course, one
expects major social indicators to change slow-
ly, if at all. There is evidence, however, that the
structure of social relationships in the United
States has shifted in recent decades. Putnam
(1995; 2000), in particular, has heightened inter-
est in networks by emphasizing links among
interpersonal ties, voluntary association mem-
bership, community well-being, and civic par-
ticipation. He follows a rich tradition, dating
back to de Tocqueville, in arguing that Ameri-
cans' ties to other members of their communi-

and Moody 2004) to crime (Sampson and Laub
1990).

To assess social change in American discus-
sion networks, we replicated the 1985 network
questions in the 2004 GSS, using the same
question wording and highly similar data col-
lection procedures. In this article, we first out-
line what we know about the characteristics of
the GSS questions — what kinds of networks
they tap, with what reliability and validity, and
what kinds of issues they leave unanswered.
We then compare the basic characteristics of
these core discussion networks at the two time
points, 1985 and 2004. ' Given that the differ-
ences, especially in network size, are very large,
we consider methodological factors that might
be biasing our results, and we provide data on
these issues when possible. Finally, we decom-
pose the differences in major network charac-
teristics into meaningful methodological and
substantive sources. We conclude with a dis-
cussion of the potential importance of our find-
ings.

CORE DISCUSSION NETWORKS: WHAT
KINDS OF TIES ARE WE MEASURING?

The Questions

When researchers study interpersonal environ-
ments, a key issue is what type of relationship
they want to measure. The ideal, of course,
would be to assess several types of relationship
(e.g., friend, coworker, advisor) and then to use
those multi-layered data to find common pat-
terns (see Fischer 1982 for an excellent exam-
ple). Given the time constraints of a national
face-to-face survey, the 1985 GSS instead

1 The GSS asked the same question in 1987 as part
of a module on political participation. In 1987, how-
ever, the survey did not ask sociodemographic char-
acteristics and interconnections among network alters.
The only network tie characteristics assessed were

SOCIAL ISOLATION IN AMERICA 355

focused on a relation that was general, cogni-
tively definable, and significant: it asked peo-
ple with whom they discussed personally
important topics.

In his earlier study of California communi-
ties, Fischer (1982) used a similar question
about discussing personal matters. He found
that this relationship elicited relatively strong
personal ties with a good representation of both
kin and non-kin. These close relationships have
theoretical importance because they are cen-
tral in social influence and normative pressures
(Burt 1984:127), and have strong conceptual
connections to earlier survey measures of best
friends and other close socio-emotional ties.
Different ways of asking about important, close
interpersonal relationships (often called strong
ties) tend to be convergent. 2 Many ways of ask-
ing such questions get the same close ties.

These close ties are only a small subset of a
person's complete interpersonal environment,
which also includes a much larger array of weak
ties, which are more distant connections to peo-
ple. Weak ties may occur in just one institutional
context or may connect us to people who are less
like us in many ways (demographically, politi-
cally, or culturally; see Granovetter 1973;
McPherson and Smith-Lovin 1981). Estimates
of the larger network of weak ties range between
150 (Hill and Dunbar 2003) to more than a
thousand (see review in Marsden 2005).

In 2004, we replicated a substantial subset of
the network questions. Specifically, the 1985
and 2004 GSS asked the following questions:

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 first names or initials. IF LESS THAN 5
NAMES MENTIONED, PROBE: Anyone else?
Please think about the relations between the
people you just mentioned. Some of them may be
total strangers in the sense that they wouldn't rec-
ognize each other if they bumped into each other
on the street. Others may be especially close, as

Are they especially close? PROBE: As close or
closer to each other as they are to you?

The survey then asked about demographic
characteristics of the discussion partner: whether
the partner was male or female, his or her race,
his or her education and age, and some aspects
of the respondents' relationship with the dis-
cussion partner. Then, the interviewer asked
more about the character of the relationship:

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 exam-
ple, 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 of the ways
that person is connected to you.

How is (NAME) connected to you? PROBE:
What other ways? (The options were presented
on a card: Spouse, Parent, Sibling, Child, Other
family, Co-worker, Member of group, Neighbor,
Friend, Advisor, Other).

What These Questions Measure
(and Miss)

People's reports of their connections with other
people are not perfect reflections of their actu-
al interactions (Bernard, Killworth, and Sailer
1 982). On the other hand, people are quite good
at remembering long-term or typical patterns of
interaction with other people (Freeman,
Romney, and Freeman 1987). Therefore,
answers that respondents give to network ques-
tions on surveys often represent their typical
interpersonal environment rather than whatev-
er researchers specifically asked them. As one
might expect, respondents report frequently
contacted, close, core network ties with those
whom they have many types of relationships
more reliably than they do more distant, simple
relations (Kogovsek and Ferligoj 2004). These
close ties are also more accessible in memory
and tend to be listed first in a survey response
(Brewer 1995; Burt 1986; Verbrugge 1977).

Snrin-pmnrinnal tips tpnri tn he nampri mnre

356 AMERICAN SOCIOLOGICAL REVIEW

complete network list generated with the help
of extensive probes. The people most likely to
be mentioned in the GSS question are strong,
close ties who are more connected to others in
the network (because one name helps the
respondent to recall others). Ruan (1998) exam-
ined the overlap of names generated by the GSS
question and other network questions based on
exchange relations in China. She found that the
GSS discussion question accounted for an
important part of a Chinese personal network.
The people with whom the Chinese respon-
dents discussed important matters were also
likely to spend leisure time with the respon-
dents and to be their confidants for personal
matters. The respondents expected them to offer
substantial help or to possess important social
resources. Similarly, Burt (1997), in a study of
managers, found that the GSS question elicit-
ed high overlap with people whom the managers
socialized with informally and considered their
most valued contacts, and who they would want
to ask for advice if they were considering a job
change. These findings reinforce our sense that
the important-matters question elicits the core,
frequently accessed interpersonal environments
that people use for sociality and advice, and
for socio-emotional and instrumental support.
While clarifying what the GSS question
measures, we should also be clear about what
it does not measure. Most obviously, it does
not measure what people talk about in their
relationships. Several studies have asked this
interesting question to help fill in the content
behind these discussion networks (Bailey and
Marsden 1999; Bearman and Parigi 2004;
Straits 2000). The studies agree that important
matters vary dramatically from respondent to
respondent, encompassing relevant personal
matters (intimate relationships, finances, health,
hobbies, and work problems), as well as more
general topics such as political issues. They
also agree that there are significant respon-
dent-alter interactions in what types of topics

arp rnrwirlprpd imnnrtnnt (Rparman anr\ Pnriai

about a specific instance of discussion of a par-
ticular important matter. Reinforcing this view,
Bearman and Parigi (2004) found that some
people cited apparently mundane matters like
getting a hair cut when asked the topic of their
latest discussion about important matters.
Luckily, Bailey and Marsden (1999) also found
that measures of key network characteristics
(e.g., density, range, heterogeneity) tended not
to vary across different interpretations of the
question.

In summary, the GSS network question about
those with whom one discusses important mat-
ters elicits a close set of confidants who are
probably routinely contacted for talk about both
mundane and serious life issues, whatever those
might be for a given respondent. They represent
an important interpersonal environment for the
transmission of information, influence, and sup-
port. We would be unwise to interpret the
answers to this question too literally (e.g.,
assuming that a specific conversation about
some publicly weighty matter had occurred in
the past six months), but these answers do give
us a window into an important set of close, rou-
tinely contacted people who make up our
respondents' immediate social circle.

DATA AND ANALYSES

The GSS is a face-to-face survey of the non-
institutionalized United States adult popula-
tion. 3 The 1985 and 2004 surveys used the same
questions to generate the names of confidants
and identical procedures to probe for addition-
al discussion partners. Therefore, the survey
responses represent a very close replication of
the same questions and procedures at two points

3 The GSS uses a multistage probability sampling
design, based on the U.S. Census. Therefore, the
1985 survey was based on the 1980 Census data,

SOCIAL ISOLATION IN AMERICA 357

in time, representing the same underlying pop-
ulation in 1985 and 2004.

Measures

We use the same measures of network charac-
teristics that Marsden (1987: 123-24) used in his
description of the structure of 1985 American
interpersonal environments. Size is the number
of names mentioned in response to the "name
generator" question. Since family members and
non-kin are fairly distinct institutional bases of
connectedness, Marsden (1987) focused his
analysis on the kin and non-kin composition of
these networks. We present these comparisons,
and the distribution of ties across the entire
range of possible relationships measured by the
GSS question (Spouse, Parent, Sibling, Child,
Other family, Coworker, Member of group,
Neighbor, Friend, Advisor, Other).

Marsden (1987) also was concerned about the
range or concentration of the interpersonal envi-
ronment, recognizing the well-known fact that
tightly connected, closed interpersonal envi-
ronments tend to be made up of similar others
and to provide fewer independent sources of
information. The contrast between range and
concentration also affects normative pressures —
both in terms of pressure to conform and the
responsibility for support in times of need. Like
Marsden, we use density of the interpersonal
network as an indicator of network concentra-
tion (the inverse of range). It is defined as the
mean intensity of tie strength among the dis-
cussion partners mentioned. The GSS data are
coded if the respondent reports that two of his
or her confidants are total strangers, 1 if they are
especially close, and 0.5 otherwise. We also
include additional measures of tie strength,
duration, and frequency of contact With the per-
son mentioned. Tie duration was measured with
a question about how long the respondent had
known his or her confidant. Frequency of con-
tact was measured by asking how often the

Analyses

We begin with an analysis that directly parallels
Marsden (1987), the much-cited description of
the interpersonal environments published in the
American Sociological Review for the 1985
data. In each case, we first replicated Marsden's
(1987) analyses on the unweighted 1985 GSS
data. We then applied weights to make the data
representative of the national population. 4 To
describe the basic parameters of discussion net-
works, we replicate the Marsden (1987) tables
using appropriate weights for both 1985 and
2004. Then, we decompose the difference in
core discussion network size using analyses
that allow us to control for demographic changes
across the two decades, to examine some pos-
sible changes in reactions to the survey process,
and to check for interactions of these variables
with year. The negative binomial regression
analysis (a change from Marsden 1987),
acknowledges the fact that our dependent vari-
able is a count variable. Finally, we use logistic
regression analysis to distinguish social iso-
lates and those who report at least one discus-
sion partner.

RESULTS

Network Size

The major finding of this study is in the first
two columns of Table 1: the number of discus-

4 We note that the 1985 results in our tables differ
very slightly from those of Marsden (1987). The
GSS sampling frame actually selects households
within blocks; the survey therefore must be weight-
ed by the number of adults in the household eligible
for the survey in order to constitute a representative
sample of individuals in the population. Marsden
(1987) presented statistics based on an unweighted
sample. In 2004, the weighting scheme was slightly
more complicated. After an initial round of data col-
lection was completed, half of the non-contacted

358 AMERICAN SOCIOLOGICAL REVIEW

Table 1 . Size of Discussion Networks, 1 985 and 2004 b

Total Discussion Network

Kin Network 3

Non-Kin Network 3

Network Size

1985

2004

1985

2004

1985

2004

10.0%

24.6%

29.5%

39.6%

36.1%

53.4%

15.0%

19.0%

29.1%

29.7%

22.4%

21.6%

16.2%

19.2%

21.0%

16.0%

18.1%

14.4%

20.3%

16.9%

11.7%

9.4%

13.2%

6.0%

14.8%

8.8%

5.8%

4.0%

6.8%

3.1%

18.2%

6.5%

2.8%

1.3%

3.4%

1.4%

5.4%

4.9%

—

Mean

2.94

2.08

1.44

1.12

1.42

.88

Mode

3.00

.00

1.95

2.05

1.41

1.38

1.57

1.40

Note: N (1985) = 1,531; N (2004) = 1,467.

" Information on kinship was collected on the first five alters cited. Therefore, the sum of kin and non-kin alters

is not equal to the overall network size distribution.

b In all tables for this paper, cases are weighted to reflect the population. Weight variable for 1985 is a function of

the number of adults in the household (ADULTS), while the weight variable for 2004 is WT2004NR.

sion partners in the typical American's interper-
sonal environment has decreased by nearly one
person (from a mean of 2.94 to a mean of 2.08).
The modal number of discussion partners has
gone from three to zero, with almost half of the
population (43.6 percent) now reporting that they
discuss important matters with either no one or
with only one other person. The decrease is espe-
cially marked among those who report four or
five discussion partners: these respondents have
gone from a third of the population (33.0 percent)
to only 15.3 percent of the population. The small
number of people who report very large discus-
sion networks (six or more) has decreased less
markedly, from 5.4 to 4.9 percent.

The next columns of Table 1 show that this
marked social change has occurred in both kin
and non-kin discussion partners. 5 Both have
dropped from a mode of 1 to a mode of 0. Since
both kin and non-kin discussion partners have
gone down, the proportion kin has increased
only moderately across the 19-year span. The

average proportion kin has gone up from 0.49
to 0.54). Marsden's (1987) generalization that
American's core discussion networks are heav-
ily constituted by family still holds.

All of the changes described in Table 1 are
statistically significant (as is the change in pro-
portion kin). The distributions on all three vari-
ables differ significantly from 1985 to 2004, and
the means are all significantly smaller in 2004.
Indeed, it is easier to list the few things that
haven 't changed: the standard deviations of all
three variables have remained relatively stable,
and are not different by year.

Types of Relationships

Table 2 looks in more detail at the types of rela-
tionships that the respondents have with their
confidants, to allow us to see where this large
social change is occurring. The top panel shows
the percentages of respondents who mentioned
at least one discussion relationship of each type.
Since the overall discussion network size has
aone down dramatically, we exnect that the ren-

SOCIAL ISOLATION IN AMERICA 359

Table 2. Respondents Who Had Various Relationships with at Least One Confidant

Type of Relationship to Respondent"

1985, %(N= 1,531)

2004, %(N= 1,467)

No Confidant

Spouse

Parent

Sibling

Child

Other Family Member

Coworker

Comember of group

Neighbor

Friend

Advisor

Other

Spouse is only Confidant

At Least One Non-spouse Kin

At Least One Non-kin Confidant

10.0
30.2
23.0
21.1
17.9
18.2
29.4
26.1
18.5
73.2
25.2
4.5

5.0
58.8
80.1

24.6**

38.1**

2 j 1 **

14.1**

10.2**

11.8**

18.0**

11.8**

7 9**

50.6**

19 2**

31**

9.2**

42.9**

57.2**

Note: The table displays, for example, "What percent of the sample mentioned a spouse/parent/etc. as a person

with whom they discussed important matters?"

a Since more than one type of relationship can be mentioned for any given discussion partner (e.g., a coworker

can also be a co-member of a group, an advisor and a friend), the percentages do not sum to 100.

** p < .01 (two-tailed tests).

only slightly (from 23.0 to 21.1 percent).
Notable for their sizeable decreases are co-
member of a voluntary group and neighbor,
both representing types of community ties that
have been stressed in the public policy debate
over civic engagement (e.g., Putnam 2000).

The relationships labeled "other," while small
in number, are an interesting residual category.
While unmarried partners are included in the
spouse/partner relationship, some respondents
do not consider the family of a partner to be part
of the respondent's own family. So, a boyfriend's
mother, a girlfriend's mother, or a partner's son-
in-law appear here as an uncoded relationship
type (rather than being placed by the respondent
into the category "other family"). Similarly, ex-
family members no longer have family status for
some respondents. Respondents reported dis-
cussing important matters with ex-spouses,
spouse's ex-spouses, son's father, and such.
Several respondents mentioned support people

Since our interest in these close personal
contacts is driven partly by their ability to shape
flows of information, influence, and affiliation,
the bottom panel of Table 2 shows the percent-
ages of respondents who have networks with dif-
ferent levels of reach. In addition to the large
proportion of respondents who have no one to
talk to, we find that the percentage of people
who depend totally on a spouse for such close
contact has increased from 5.0 to 9.2 percent.
The proportion of people who talk to non-spouse
kin (who are likely to reside outside their own
household) has dropped (58.8 to 42.9 percent).
The most striking drop, however, is in the per-
centage of people who talk to at least one per-
son who is not connected to them through
kinship, a decline from 80.1 to 57.2 percent.
These latter ties are the most likely to bridge
socially distinct parts of the community struc-
ture, since we know that marriage and family
ties are more homophilous on class, religion,

ial

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360 AMERICAN SOCIOLOGICAL REVIEW

Table 3. Structural Characteristics of Core Discussion Networks

1985 (N= l,167 a )

2004 (N = 788 b )

Network Density

<25

9.9%

7.3%

.25-49

18.5%

11.8%

.50-74

37.9%

39.5%

>.74

33.7%

41.4%

Mean

.60

.66

.33

Mean Frequency of Contact (days per year)

6-12

3.7%

3.0%

> 12-52

15.3%

10.6%

>52-365

81.0%

86.4%

Mean

208.92

243.81

117.08

114.86

Length of Association (in years)

>CM1.5

12.1%

10.7%

>4.5-8+

87.9%

89.3%

Mean

6.72

7.01

1.34

1.00

Age Heterogeneity (standard deviation of age of alters)

25.8%

29.1%

5-<10

24.6%

19.7%

10-<15

24.3%

23.9%

>15

25.3%

27.3%

Mean

10.35

10.34

6.96

8.1

Population Age Heterogeneity

20.89

18.37

Education Heterogeneity (standard deviation of alters' educations)

0-1

31.9%

34.7%

>l-2.5

41.0%

45.2%

>2.5

27.0%

20.1%

Mean

1.77

1.48

1.52

1.38

Population Educ Heterogeneity

3.59

3.17

Race Heterogeneity (Index of Qualitative Variation)

91.1%

84.5%

8.9%

15.4%

Mean

.05

.09

.18

.26

Population IQV

.34

.53

Sex Heterogeneity (Index of Qualitative Variation)

23.8%

24.2%

.01-.90

39.9%

37.6%

>.90

36.3%

38.1%

Mean

.67

.68

.43

.46

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1 no

SOCIAL ISOLATION IN AMERICA 361

very densely interconnected, with mean densi-
ties of 0.60 and 0.66 respectively in 1985 and
2004. This density is the average level of inter-
connection among named confidants. Recalling
that a code of 1 represents the confidants being
closer to each other than they are to the respon-
dent, these networks are quite tightly woven.
This pattern was noted by Marsden (1987: 126)
and remains strong in 2004. There is a slight
shift toward even more interconnected networks
in 2004, a pattern that is supported by analyses
of frequency of contact and duration of tie. The
typical respondent now sees his or her close
confidant more than once a week, on average,
and has known him or her for more than seven
years. In general, the core discussion networks
in 2004 are more closely tied to each other, are
more frequently accessed, and are longer-term
relationships. Even more than in 1985, the dis-
cussion networks we measure in 2004 are the
closest of close ties.

We can also examine the character of the
interpersonal environments by examining the
diversity of the people mentioned as core dis-
cussion partners. Table 3 also looks at the het-
erogeneity of confidants in terms of age,
education, race, and sex. Here, again, we see a
picture of relative stability. The mean hetero-
geneity of the discussion networks is signifi-
cantly less than the heterogeneity of the overall
population, reaffirming the well-known finding
that networks are homophilous (McPherson et
al. 2001). The relatively subtle changes in the
diversity of the discussion networks seem to
mirror the demographic changes in the popu-
lation. Age and education heterogeneity have
gone down in the general population, mainly
because of cohort succession, and the diversi-
ty of discussion networks has gone down slight-
ly to reflect that fact. Racial diversity has gone
up in the population (through immigration and
disparate fertility rates), and has increased in dis-
cussion networks as well. (Analyses not report-
ed here also indicate that more people now have

a rnnfiHant nf annthpr rarp That iq rp^nnnHpnt

than they are to the respondent). In addition,
having kin in one's network tends to increase
contacts across age categories (through con-
tacts with grandparents, parents, or children),
educational strata (because of cohort differ-
ences in educational stock), and sex (because of
the heterosexual nature of marital unions and the
sex composition of sibship), while it reduces
heterogeneity of network ties on race, religion,
geographic origin, and other matters
(McPherson et al. 2001; Marsden 1987:
Table 2).

Comparing 1985 and 2004, we see that most
of the effects of the proportion of kin in one's
core discussion network on the interconnect-
edness and diversity of network contacts are
quite stable over the time period. Since these pat-
terns are relatively well known, we present them
in an Online Supplement and comment only
on significant changes here (see Online
Supplement on ASR Web site: http://www2.
asanet.org/journals/asr/2006/toc051.html).
Having kin as confidants tends to make one's
network more interconnected and dense — since
kin tend to know each other and perhaps be
close. This effect, however, is somewhat less
marked in the 2004 data than in the 1985 data.
Regressing density on proportion kin produces
an OLS coefficient of .26 in 2004, as compared
to .36 in 1985; the proportion kin coefficient
interacts significantly with year). 7 Furthermore,
the predicted value of density when a network
has no kin in it has increased in 2004 compared
to 1985, indicating that even non-family dis-
cussion partners are now more likely to know
each other and be close.

The effect of kin on age heterogeneity in dis-
cussion networks has increased, probably
because of changes in cohort structure.
Networks of kin are more age diverse now than
in the 1980s, while discussion networks with-
out kin are more age homogeneous. The largest
change, by far, is in the coefficient-related pro-
portion kin in the discussion network to educa-
tional hptprrmpnpit\r A/TarcHpn MQR7- Tahlp 1\

362 AMERICAN SOCIOLOGICAL REVIEW

finds a large positive OLS coefficient (A2,p <
.01). The weighting by adults in the household
changes this coefficient much more than most
other findings, reducing the effect to .30 (still
statistically significant at^ < .01). The impact
of kin on educational diversity is much lower in
2004 (a coefficient of .20) and is no longer sta-
tistically significant. Both kin and non-kin net-
works have gotten less educationally
heterogeneous by 2004 — primarily because of
cohort succession and the increasing educa-
tional stock of the population as a whole. The
difference in cross-educational contact, poten-
tially important for both the framing of issues
and the flow of information, no longer varies
significantly if one has only kin for confidants
or no kin at all in one's discussion network.

Demographic Variation in Networks

Marsden (1987) also examined how important
demographic categories varied in terms of their
interpersonal environments. Table 4 here repro-
duces some of the most important analyses
shown in Marsden's (1987) Tables 3 and 4. We
use OLS to see how age, education, race, and
sex influence the size, kin composition, and
density of one's core discussion networks.

Age, which structured networks significant-
ly in 1985, has very little impact on contempo-
rary confidant networks. Marsden (1987:
127-28, Table 3) found a curvilinear pattern,
with network size (especially non-kin confi-
dants) dropping off quite precipitously with
increasing age and the proportion kin being
somewhat higher among younger respondents
and the elderly ages. In contrast, age is not
strongly related to size or kinship composition
in 2004. None of the nonstandardized coeffi-
cients regressing the network characteristics on
age and age squared is statistically significant,
and the multiple correlation between age, age
squared, and network characteristics is not sig-
nificantly different from zero. Clearly, there
has heen cohort succession since 1 985: the verv

more educated people have a lower proportion
of kin in their networks than people with less
education.

In the confidant networks of men and women,
we see that women still have significantly more
kin in their networks than men do, but they no
longer have fewer non-kin confidants than men.
Since the size of both the kin and non-kin coef-
ficients has gotten smaller from 1985 to 2004,
we find that women no longer have a signifi-
cantly higher proportion of kin in their net-
works when compared with men. Since the
kin-dominated nature of women's networks is
one of the staples of the social capital literature
(c.f, Moore 1990), this social change is poten-
tially important. It is especially noteworthy that
the shift occurs not because women are dropping
kinship ties, but rather because they are achiev-
ing equality with men in non-kinship ties.
Unfortunately, as with growing wage equality,
the equity is being achieved by men's shrinking
interconnection with non-kin confidants rather
than by women's greater connection to the world
outside the family.

Race continues to have a broad impact on net-
works in American society. Both blacks and
other-race respondents have smaller networks of
confidants than white Americans (the reference
category). This pattern is most apparent in kin-
ship networks, which are markedly smaller
among non-whites.

A Preliminary Summary

of Social Change in Networks

In spite of a large literature on declining civic
engagement and neighborhood involvement,
we began this analysis with the expectation that
networks of core confidants would be a stable
feature of one's interpersonal environment.
Given the close, densely interconnected nature
of the ties generated by the GSS question, it
seemed unlikely that the typical American would
not mention several people in response. We

SOCIAL ISOLATION IN AMERICA 363

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364 AMERICAN SOCIOLOGICAL REVIEW

membership and neighbor have decreased dra-
matically.

Such a large, unexpected social change rais-
es immediate questions. Therefore, in the next
section we explore some reasons why the appar-
ent difference between 1985 and 2004 might be
artifactual. We also review other trends that
might support or question our results.

COULD SUCH A LARGE
SOCIAL CHANGE BE REAL?

Social change is best measured when bench-
marks are frequent. Since our measurements
are 19 years apart, we have no way to assess
directly whether or not the dramatically small-
er 2004 networks are part of a slowly develop-
ing trend. We therefore must consider threats to
validity and look at related data to see if other
trends might show similar patterns.

Study Design

The most common threat to trend measurement
is change in the questions themselves. The GSS
asked the same question in 1985 and 2004.
While the important matters that respondents
discussed may have shifted with demographic
characteristics or historical context, there is no
reason to expect that the 2004 important-mat-
ters question would not elicit the close, fre-
quent confidants that it did in 1985. Interviewer
training and probe patterns also were very sim-
ilar across the two surveys. The GSS imple-
mented a number of changes in sampling frame
and survey procedures during the two-decade
period in question, but these seem very unlike-
ly to have created the observed pattern. 8

Context

Question order is a vexing, important, and
understudied aspect of survey design (see review
in Smith 1989). Context effects are generally not

large, however, and tend to be concentrated
within modules of questions on similar con-
tent. In methodological experiments conducted
in 1988, when the GSS core questions were
changed, Smith (1989) estimated that only six
out of 358 questions showed real context effects.

For questions like the ones of interest here,
however, preceding questions can influence
what one thinks of as important matters (Bailey
and Marsden 1999; Bearman and Paragi 2004)
and, to a lesser extent, which alters one names
(Straits 2000). In 1985, the network questions
were preceded by a battery of questions on reli-
gion. In 2004, they were preceded by a module
of questions on voluntary group membership.
While not identical, the fact that a large pro-
portion of the voluntary sector is composed of
religiously affiliated associations (Bonikowski
and McPherson 2006) means that the connec-
tions that would be cognitively primed would be
somewhat similar in both cases. If there were a
bias introduced by this contextual feature, one
suspects that it would lead to overreporting of
co-membership relationships in the 2004 net-
work data (since the groups of which the respon-
dent and his/her alters might have been
co-members had just been reviewed, and the
topics that they invoked presumably primed).
Recall from Table 2, however, that co-mem-
bership relations declined more than other types
of relations.

A more serious possibility is that the volun-
tary organization questions in 2004 had a train-
ing effect on respondents — effectively teaching
them that mentioning a larger number of affil-
iations in response to an initial question would
then lead to more questions about each men-
tioned connection. 9 Luckily, the GSS network
questions were partially repeated in 1987 in a
module on political participation. In 1987, the
network question appeared just after the battery
of questions on voluntary association. (In this
case, the network question was not followed by
queries about the alter's characteristics, but
instead was narrowed to a focus on political

SOCIAL ISOLATION IN AMERICA 365

1985 and 2004.) In supplement data, we com-
pare the limited analyses that can be replicated
comparing 1987 and 2004, separated by 16
years and both preceded by voluntary associa-
tion modules (see Online Supplement on ASR
Web site). In these replications, we again find
a dramatic drop in network size (from 2.63 in
1987 to 2.08 in 2004,/; < .01) and a dramatic
increase in the proportion of respondents with
no core confidants (4.5 percent in 1987 and
24.6 percent in 2004,/; < .01). There may have
been some tendency for the voluntary associa-
tion context effect to suppress very large net-
works. Comparing the 1987 data to the 1985
data, we see fewer networks of sizes three, four,
five, and more. Yet the voluntary association
context decreased the number of people who
reported no confidants; that proportion is actu-
ally smaller in the 1987 data than in the 1985
data (4.5 percent as compared with 10.0 per-
cent).

The relationship between voluntary associa-
tion membership and network size is positive
and roughly the same size in both surveys (a cor-
relation of .22 in 1987 compared to a correla-
tion of .18 in 2004). This relationship is a
substantively reasonable one: there is a large lit-
erature on the interrelationship of networks and
voluntary groups (McPherson 1983, 2004;
McPherson and Ranger-Moore 1991;
McPherson, Popielarz, and Drobnic 1992).
Ideally, of course, one would want an experi-
ment embedded in the survey design that
assessed how context affected the network ques-
tions. In time, such a measure of context effect
should be possible. The National Science
Foundation has funded a re-interview of the
2004 GSS respondents to further link their net-
works and voluntary association memberships
through a life history calendar (BCS 052767 1,
"Niches and Networks: Studying the Co-evo-
lution of Voluntary Groups and Social
Networks," $746,000). These interviews will
be conducted in the fall of 2006, two years after

might attempt to speed the survey process along
by saying that they have few (or no) entries in
the list. The GSS is a long survey, lasting over
an hour for many respondents. Therefore, one
must be concerned with fatigue effects, espe-
cially if these effects differed in 1985 and 2004.

The network items occurred near the end of
the survey in both years. The GSS asks a core
of sociodemographic and social trend questions
in each year, 10 followed by modules of questions
on various topics. In 1985, the first network
question was question 127 out of 148 total ques-
tions. In 2004, the name generator question was
also numbered 127, but this has less meaning
in a CAPI survey where different questions take
on different positions depending on skip pat-
terns. It occurred, however, after 109 questions
in the core and a module of questions about
membership in voluntary associations.

The GSS has the interviewer rate the coop-
erativeness of the respondent immediately after
the face-to-face session is completed (soon after
the network questions in both years).
Respondents are categorized as interested/
friendly, cooperative, restless/impatient, or hos-
tile. The 2004 respondents were no more like-
ly to be impatient or hostile than were the 1985
respondents (less than 4 percent in both years).
The great majority of respondents were rated in
the most positive category (interested/friendly)
in both years (79.3 and 82.2 percent in 1985 and
2004 respectively).

As we expected, cooperativeness is strongly
related to the number of people who are report-
ed as confidants, with hostile respondents
reporting almost two fewer confidants than
interested and friendly respondents. There was
no statistical interaction, however, between the
cooperativeness variables and survey year in
predicting the number of discussion partners
mentioned. To the extent that uncooperative-
ness leads to underreporting of network ties, this
factor seems to have operated in similar ways
in both survey years. We also note that some of

thp rplatinnshin hptwppn rnnnprativpnpsn and

366 AMERICAN SOCIOLOGICAL REVIEW

situation of a face-to-face interview may also be
more sociable in other settings.

We also constructed an index of how many
questions prior to the network module had miss-
ing data for each respondent. Our logic was
that refusal to answer preceding questions might
be a behavioral indicator of fatigue or non-
cooperativeness. Indeed, the number (out of 10)
questions coded missing immediately prior to
the network module is correlated -0.16 with the
number of network alters mentioned (p < .01).
We therefore control for this index of missing
data in our multivariate analyses of network

Convergent Data from Other Sources

In the case of most major social changes,
researchers can triangulate from multiple data
sources at multiple time points to establish an
overall pattern with some certainty. Since schol-
ars have rarely measured networks in a way that
can be generalized to the national population,
we have fewer resources here. There are, how-
ever, two types of evidence that might reinforce
the data that we present.

The first source of convergent data is
Bearman's and Parigi's (2004) finding that 20
percent of the North Carolinians that they inter-
viewed in 1997 have no one with whom they dis-
cuss important matters. The proportion of people
who report no confidants in the North Carolina
study is consistent with the trend between the
10.0 percent estimated from the 1985 GSS sam-
ple and the 24.6 percent estimated from the
2004 sample. In supplemental data, we also
note that the 1987 GSS data show a movement
toward a lower network size (see Online
Supplement on ASR Web site).

On the other hand, some telephone surveys
of the national population asking questions
about the number of close friends show rather

different results. In 1990, for example, the
Gallup Poll found that only 3 percent of their
sample reported no close friends; only 16 per-
cent had less than three friends. While there
are many differences between the Gallup and
GSS surveys, this raises the interesting question
of whether the important-matters question gets
at closer, core ties than the concept of close
friend. Another recent telephone survey by Pew
also found much larger numbers of core or close
friends, when it asked about a combination of
types of contact (Boase et al. 2006). Both of
these surveys alert us to the possibility that
respondents might be interpreting "discuss" in
a literal way, and not including some types of
personal contact (see Conclusions section). On
the other hand, the Pew survey has a response
rate of 35 percent, while the GSS consistently
gets more than 70 percent of its sampled units.
Our analyses (not reported here, but available
from the authors) of the 2004 weights used in
the GSS indicate that easily reached respon-
dents are quite different from difficult-to-inter-
view people in terms of their interpersonal
environments. This fact reinforces the impor-
tance of response rates in studies of affiliation,
social networks, and civic participation.

The second area where we look for conver-
gence is other trend data reported by the large,
hotly contested literature on civic engagement.
Putnam (1995, 2000) raised the issue of declin-
ing embeddedness in civic and neighborhood
associations to the attention of both policy-
makers and scholars (especially in political sci-
ence, where networks had not been a central
topic previously). While there has been sub-
stantial debate about his data and the down-
ward trends that they indicate (c.f, Fischer
2005; Paxton 1999; Rotolo 1999; Rotolo and
Wilson 2004; Sampson 2004), the decline that
he reports in socializing among neighbors and
general participation in social life beyond the
level of the nuclear family fits well with our

observations that association co-members,

11 Since the index considers different questions in n piohhnr« and pvtpndpd fqmilv arp mpntinnpd

SOCIAL ISOLATION IN AMERICA 367

to the social changes that we observe. For exam-
ple, the decline in socializing with neighbors has
been about 3 percent over the past two decades.
Respondents in 2004 are somewhat less likely
than those in 1985 to report that they can trust
other people, think that they are fair (as opposed
to taking advantage), and think that they are
helpful (as opposed to looking out for them-
selves). The changes in these variables, howev-
er, are in the order of 2 percent (fair) to 9.6
percent (helpful) — again, small relative to the
drop that we see in core network size.

Demographic Change as a
Source of Network Change

Of course, the demographic characteristics of
the country have changed considerably in the
two decades. Some of those changes could have
resulted in a shrinking network size even in the
absence of non-demographic social change. As
the population gets older and more racially
diverse, we would expect networks to get small-
er, since older people and racial minorities have
smaller networks, on average. On the other

hand, the increasing education of the population
should tend to increase network size. To assess
the extent to which basic demographic changes
have altered the landscape of interpersonal envi-
ronments, we now move to a multivariate model
to examine change from 1985 to 2004.

CHANGE NET OF DEMOGRAPHIC AND
METHODOLOGICAL FACTORS

We use negative binomial regression to model
the size of discussion networks, because our
dependent variable is a count of network alters.
Here, data from both the 1985 and 2004 GSS
are combined, with the survey year acting as an
independent variable in the analysis. Table 5,
Model I, illustrates the most important social
change documented by our earlier analyses of
discussion networks: the number of confidants
has decreased significantly over the period
between the two surveys. This negative binomial
coefficient of -.356 (evaluated with the Y-inter-
cept) corresponds to a drop of .86 network alters
by 2004 (c.f, row 8 of Table 1, results round-
ed). The coefficients in all models for Wave

Table 5. Multivariate Models of Discussion Network Size and Social Isolation

Model

Dependent Variable

Dependent Variable:

Discussion Network Size

No Discussion Partners

(Negative Binomial Regression)

(Logistic Regression)

Independent Variable

III

Constant

1.078

1.150

.477

-2.144

-1.297

Wave(l =2004)

-.356

-.329

-.407

1.374

214NS, b

Cooperative (Compared to Friendly/Interested)

—

-.225

-.145

.126 NS

.132 NS

Restless/Impatient

—

-.667

-.585

1.295

1.308

Hostile

—

-1.121

-.985°

2.005

2.016

Number Missing in Previous Module

—

-.257

-.198

.372

.376

Education (in yrs)

—

.059

-.087

-.158

Education* Wave

—

.099

Female

—

.071 c

-.194 NS

-.195 NS

Age a

—

-.002

.016

.015

Currently Married

—

.061 c

-.256

-.253

368 AMERICAN SOCIOLOGICAL REVIEW

(the 1985-2004 contrast) are a test of the null
hypothesis that differences in network size
between the two surveys are due to sampling
error.

Model II adds the indicators of fatigue and
hostility that we suspect may lead respondents
to underreport their network ties. The more hos-
tile the respondent gets, the more he or she is
likely to report a small network. Having miss-
ing data on questions that precede the network
questions serves as an additional indicator of
survey problems. Controlling for these data
issues does not, however, significantly reduce
the drop in discussion network size from 1985
to 2004.

Controlling for demographic factors actual-
ly increases the estimated difference in net-
work size over the 19-year period (Model III).
This effect occurs because education is posi-
tively associated with network size, and educa-
tional levels have increased over time. This
effect more than offsets the declines in network
size due to other factors such as the declining
proportion of the population that is married and
the growing minority population.

More educated and younger people have sig-
nificantly larger discussion networks, as do
women. Network size gradually shrinks with
aging, and non-white Americans have fewer
network resources. Marriage draws one into
networks of people with whom one discusses
important matters (notably one's spouse, the
most often-named type of relationship for the
discussion partner). 12

Of course, there are many controls that we
could implement. The results in Table 5 repre-
sent the major, stable, statistically significant
demographic sources of confidant networks.
Some of the logically plausible socio-demo-
graphic variables are not important sources of
network variation in these data. For example, the
opportunity structures represented by number of
siblings, number of children, and number of
adults in the household do not significantly
affect the number of confidants (possibly

resented as hours worked per week or as dummy
variables for full-time and part-time work) does
not have an effect. Geographic mobility does not
appear to have an impact, although our ability
to explore this factor is limited by the fact that
the "size of place" variable has not yet been
added to the 2004 GSS. 13 Neither size of place
of residence at age 16 nor whether or not the
respondent has moved geographically since age
16 has an effect. While a full exploration of the
non-demographic sources of confidant networks
is beyond the scope of this article, some com-
monly used predictors like the number of hours
spent watching television are also unimportant
(Putnam 2000). Therefore, we conclude that
the large drop in confidant networks between
1985 and 2004 in these data is unlikely to be a
result of population shifts on other variables.

Since negative binomial regression coeffi-
cients are not as intuitively interpretable as OLS
coefficients, we offer the following predicted
values from Table 5 as illustration of our main
result. In 1985, a white married 25-year-old
male high school graduate who was an inter-
ested, friendly respondent to the survey, and
who had no missing data on any of the 10 items
preceding the network module, would be expect-
ed to have slightly more than three confidants
(3.3) with whom he discussed important mat-
ters. In 2004, an interested, friendly fellow with
the same demographic characteristics would
have reported a network more than one alter
smaller (2.2). Another way of viewing the same
comparison would be to age our friendly fellow
by the 19 years of the study (from 25 to 44),
leading to an even smaller network of 2. 1 alters.

The resources represented by core networks
mirror other major class divides in our society.
Net of all other factors, increasing education
sharply increases the number of discussion part-
ners that a respondent reports, from roughly
1.5 alters for a person with the lowest level of
education in 1985, to around five alters for such
a person at the highest level of education. The
differences for 2004 are smaller, but iust as

SOCIAL ISOLATION IN AMERICA 369

alters. The differences between 1985 and 2004,
however, remain salient even in the face of this
major divide. In 1985, high school dropouts
(with 10 years of education) had a network with
roughly 2.8 discussion partners — in the range
of a college graduate in 2004.

Figure 1 brings these stark differences in
educational trajectory to bear on the issue of kin
composition and network range. In both time
periods, education promotes discussion with
both kin and non-family members, with ties
outside the family affected most markedly. The
different slopes of these two curves mean that
at some level of educational achievement the
two curves cross. Discussion networks become
dominated by people outside one's immediate
family. In 1985, this cross occurred at around
13 years of education, a little more than a high
school diploma. Discussion networks of those
with some college comprised more non-family
than family; college graduates had more confi-
dants outside their kin group than inside it. In
2004, the non-kin ties have dropped so much
that this crossover is not predicted to occur until
a respondent has acquired post-college educa-
tion. Clearly, the net effect of these changes is

to focus and limit the reach of core discussion
networks in the general population.

THE SHAPE OF SOCIAL ISOLATION

Given the close, dense nature of core discussion
networks, one might argue that the crucial dis-
tinction is not among different network sizes but
between those who have someone to talk to and
those who report no one with whom they can
discuss matters that are important to them. In
Table 5, Model IV, we present a logistic regres-
sion analysis that contrasts those who did not
name anyone in answer to the name generator
(even after the obligatory probe by interview-
ers) and those who did name a discussion part-
ner. Most of the effects are what we would have
expected from our earlier analysis of network
size. The data issues operate in the same man-
ner — more cooperative respondents are less
likely to be socially isolated, while those who
having lots of missing data are more likely to be
isolates. More highly educated, younger, cur-
rently married people are less likely to be social
isolates.

The only notable change from Model III
here is that men are not significantly more

3.5

2.5

1.5

0.5

370

AMERICAN SOCIOLOGICAL REVIEW

likely than women to be social isolates in core
discussion networks. They may have fewer dis-
cussion partners than women, but they
nonetheless are as likely to have at least one
confidant. Similarly, other-race people are not
significantly different from whites (although
blacks are still more likely than whites to be
isolates).

In the analyses reported in Table 5, we test-
ed for all possible two-way interactions between
survey year and predictor variable. In the logis-
tic regression analysis of the probability of
being a social isolate, we found an interaction
between survey year and education. Model V
shows that interaction. The effect of education
on the probability of being a social isolate is
strong and negative in 1985 (a coefficient of -
0. 158), and becomes somewhat less negative in
2004 (-0.158 + 0.099 = -0.059).

Again, to make the logistic regression coef-
ficients somewhat more vivid, we compute the
predicted probability that our white married
25-year-old male high school graduate who is
enthusiastically participating in the survey and
leaving no missing data would have someone to
talk to about important matters in 1985. He

would be virtually assured of a discussion part-
ner (predicted probability of being an isolate =
0.04). The same type of person in 2004 would
have a more a ten percent chance of being an
isolate (predicted probability = 0.16). Do the
same mental experiment and age our 25-year-
old to 44 years of age in 2004: we find that his
probability of being an isolate would have quin-
tupled from 0.04 to 0.20.

UNEVENNESS IN THE SOCIAL
CHANGE

Given that social change rarely affects the entire
population simultaneously, the relative lack of
interactions seems somewhat strange. We there-
fore explore in more depth possible uneven-
ness in the network changes that we observe.
While the change is unusually pervasive (prob-
ably because of the 19-year gap in our assess-
ment), there are some hints about uneven change
in different social groups.

First, there is the statistical interaction
between education and year in affecting the
probability of social isolation. This interaction
is made clearer by inspection of Figure 2, which

0.35

0.3

3 0.25

1 0.2

0.15

0.1

0.05

SOCIAL ISOLATION IN AMERICA 371

plots the fitted probability of social isolation
across years of education in 1985 and 2004. As
the figure shows, there is a very sharp increase
in the probability of social isolation for all lev-
els of education, but the greatest change occurs
in the middle range of education. In 1985,
increasing education led to a sharp decline in
social isolation, while that effect is much less
evident in 2004. This change is one of the few
areas where inequality has gone down in our
society. Unfortunately, the inequality is decreas-
ing because everyone is getting worse off (if we
assume that social isolation is bad).

We also inspected the data for interesting
subgroup differences, using the intersection of
race, class, and gender as a general guide. The
decline in networks is quite uniform, but young
(ages 18-39), white, educated (high school
degree or more) men seem to have lost more dis-
cussion partners than other population groups
(from 3.5 in 1985 to 2.0 in 2004). In the next
section, we discuss the possible impact of
Internet usage on this demographic group.
Young, poorly educated (less than high school),
white women also experienced a large decline
(3.2 to 1.4 alters).

Among African Americans, a gender differ-
ence is striking. Older (60+) African American
men's networks have declined the most (from
3.6 to 1 .8). Among black women, the change is
more uniform, with the young experiencing a
larger decline than the old. Indeed, black men
over 60 are the only sector of the older popula-
tion that experienced a major decline between
1985 and 2004. Otherwise, the elderly have
been more stable than most other groups in
their core social connections. 14 This article
leaves these possible subgroup changes in core
discussion networks to future analyses.

DISCUSSION AND CONCLUSIONS

If we assume that interpersonal environments
are important (and most sociologists do), there
appears to have been a large social change in the
past two decades. The number of people who
have someone to talk to about matters that are
important to them has declined dramatically,
and the number of alternative discussion part-
ners has shrunk. In his groundbreaking study of
social networks, To Dwell among Friends,
Claude Fischer (1982:125-27) labeled those
who had only one or no discussion ties with
whom to discuss personal matters as having
marginal or inadequate counseling support. By
those criteria, we have gone from a quarter of
the American population being isolated from
counseling support to almost half of the popu-
lation falling into that category.

The American population has lost discussion
partners from both kin and outside the family.
The largest losses, however, have come from the
ties that bind us to community and neighbor-
hood. The general image is one of an already
densely connected, close, homogeneous set of
ties slowly closing in on itself, becoming small-
er, more tightly interconnected, more focused on
the very strong bonds of the nuclear family
(spouses, partners, and parents). The education
level at which one is more connected through
core discussion ties to the larger community
than to family members has shifted up into the
graduate degrees, a level of education attained
by only a tiny minority of the population. High
school graduates and those with some college
are now in a very family-dominated social envi-
ronment of core confidants.

Some of the basic parameters of discussion
network structure have moved very little in 1 9
years. Age and sex heterogeneity of ties has
remained remarkably constant, and the decline
in educational diversity seems directly linked to
the increasing education level of the population.
Racial contact in these discussion networks has
actuallv increased. Havine a network dominat-

372 AMERICAN SOCIOLOGICAL REVIEW

now kin and non-kin look similar in their edu-
cational composition.

If core discussion networks represent an
important social resource, Americans are still
stratified on education and race. Higher edu-
cation people have larger networks of both fam-
ily and non- family members, and their networks
have more of the range that tends to bring new
information and perspective into the interper-
sonal environment. Non-whites still have small-
er networks than whites. Sex, on the other hand,
seems to have lost some of its interpersonal
stratifying power in the past 19 years. While
women still have marginally larger networks
than men and have more discussions about
important matters with kin, they no longer show
a significant deficit in the number of core con-
tacts outside the family. As a result, women no
longer have a significantly more kinship-
focused discussion network than men; nor are
they significantly less likely than men to be
social isolates.

Our final estimates, corrected for response
problems and demographic shifts, are that (1)
the typical American discussion network has
slightly less than one fewer confidant in it than
it did in 1985, and (2) that in 2004 an adult, non-
institutionalized American is much more like-
ly to be completely isolated from people with
whom he or she could discuss important mat-
ters than in 1985. Given the size of this social
change, we remain cautious (perhaps even skep-
tical) of its size. The limited network data in
1987 indicate that the proportion of people who
answer "no one" and who list relatively large
numbers of confidants may be especially sen-
sitive to context effects (see Online Supplement
on ASR Web site). Given our analyses of the
highest-quality nationally representative data
available, however, our best current estimate is
that the social environment of core confidants
surrounding the typical American has become
smaller, more densely interconnected, and more
centered on the close ties of spouse/partner.

Thp tvnp« nf hriHaina tipe that mnnppt iiq tn

other literature) to guide future research. Three
explanations seem most likely.

The first two possibilities concern how peo-
ple interpret the question that we asked them,
in view of historical and cultural change. What
Americans considered important might well
have shifted over the past two decades, perhaps
as a result of major events (the attacks of 9/1 1
and the wars that followed). If people think of
"important" more in terms of national and
world-level events, more people might now
think that they have nothing important to say. 15
Since many people interpret the question as
simply asking about their close confidants
(rather than a particular discussion of important
matters), it seems unlikely that such a shift in
cultural meaning would have produced such a
strong effect. It may, however, have contributed
to the pattern.

The second possibility is that the use of the
word "discuss" in the question was interpreted
by respondents to exclude other forms of com-
munication that are becoming dominant in our
contacts with core confidants. Many more peo-
ple now use cell phones and Internet (email, list
serves, chat rooms, and instant messaging) to
contact core network members (Wellman et al.
2006; Boase et al. 2006). If people exclude
these types of communications when answering
the question, it could reduce the number of
alters reported. 16

The third possibility is the most substantive-
ly interesting. Shifts in work, geographic, and
recreational patterns may have combined to cre-
ate a larger demarcation between a smaller core
of very close confidant ties and a much larger
array of less interconnected, more geographi-

15 Bearman and Parigi (2004) found that roughly
half of their respondents who reported discussing
important matters with no one in the past six months
said that they had nothing to say.

16 The fact that cell phones and Internet commu-
nications tend to mirror other channels of commu-

SOCIAL ISOLATION IN AMERICA 373

cally dispersed, more unidimensional relation-
ships. Families, especially families with chil-
dren, may face a time bind that comes from
longer commutes and more work time
(Hochschild 1997). As more women have
entered the labor force, families have added 10
to 29 hours per week to their hours working out-
side the home (Jacobs and Gerson 2001; Hout
and Hanley 2002). The increase has been the
most dramatic among middle-aged, better-edu-
cated, higher-income families — exactly the
demographic group that fuels the voluntary
association system (McPherson 1983;
McPherson and Ranger-Moore 1991). The nar-
rowing of the education gap suggests that this
group — highly educated middle-class fami-
lies — is where the declines in the number of core
discussion ties have been sharpest. Such fami-
lies can use new technologies to stay in touch
with kin and friends — most notably cell phones
and the Internet. While these technologies allow
a network to spread out across geographic space
and might even enhance contacts outside the
home (e.g., arranging a meeting at a restaurant
or bar), they seem, however, to lower the prob-
ability of having face-to-face visits with fami-
ly, neighbors, or friends in one's home (Boase
et al. 2006; Gershuny 2003; 2and Erbring 2000;
Nie, Hillygus, and Erbring 2002). 17 Wellman et
al. (2006:10-13) note that Internet usage may
even interfere with communication in the home,
creating a post-familial family where family
members spend time interacting with multiple
computers in the home, rather than with each
other. They suggest that computer technology
may foster a wider, less-localized array of weak
ties, rather than the strong, tightly intercon-
nected confidant ties that we have measured
here.

This may not be all bad, of course, since we
know that weak ties expose us to a wider range
of information than strong, close ties. We also
know, however, that strong ties offer a wider
array of support, both in normal times (Wellman
and Worlev 1990*1 and in emergencies fHurlhurt

et al. 2000). Only geographically local ties can
offer some services and emotional support with
ease (Wellman and Worley 1990).

Whatever the reason, it appears that
Americans are connected far less tightly now
than they were 19 years ago. Furthermore, ties
with local neighborhoods and groups have suf-
fered at a higher rate than others. Possibly, we
will discover that it is not so much a matter of
increasing isolation but a shift in the form and
type of connection. Just as Sampson et al. (2005)
discovered a shift in the type of civic partici-
pation, and the Pew Internet and American
Society Report (Boase et al. 2006) showed a
shift in modes of communication, the evidence
that we present here may be an indicator of a
shift in structures of affiliation.

Miller McPherson is Professor of Sociology at the
University of Arizona and Research Professor of
Sociology at Duke University. His current projects
include a test of his evolutionary model of affiliation
with nationally representative data funded by the
Human and Social Dynamics Initiative at the
National Science Foundation. The project will create
a representative sample of voluntary groups and
study the co-evolution of group memberships and
networks over time.

Lynn Smith-Lovin is Robert L. Wilson Professor of
Sociology at Duke University. She received the 2006
Cooley-Mead Award from the ASA s Social
Psychology Section and the 2005 Lifetime
Achievement Award in the Sociology of Emotions. Her
research examines the relationships among social
association, identity, action, and emotion. Her cur-
rent projects involve an experimental study of justice,
identity, and emotion as well as work with McPherson
on an ecological theoiy of identity (both funded by
the National Science Foundation).

Matthew E. Brashears is a Ph.D. candidate in
Sociology at the University of Arizona. A past win-
ner of the Pacific Sociological Association and the
Social Psychology Section s Graduate Student Paper
Awards, he is interested in social networks and their
role in information transmission and transformation.
His dissertation focuses on examining the reciprocal
effects of attitudinal similarity and network formation.

374 AMERICAN SOCIOLOGICAL REVIEW

and Interview Context: Examining the General
Social Survey Name Generator Using Cognitive
Methods." Social Networks 2 1 :287-309 .

Bearman, Peter S. and James Moody. 2004.
"Adolescent Suicidally." American Journal of
Public Health 94:89-95.

Bearman, Peter and Paolo Parigi. 2004. "Cloning
Headless Frogs and Other Important Matters:
Conversation Topic and Network Structure." Social
Forces 83:535-57.

Bernard, H. R., P. D. Killworth, and L. Sailer. 1982.
"Informant Accuracy in Social Network Data: An
Experimental Attempt to Predict Actual
Communication from Recall Data." Social Science
Research 11:30-66.

Boase, Jeffery, John Horrigan, Barry Wellman, and
Lee Rainie. 2006. "The Strength of Internet Ties."
Washington, DC : Pew Internet and American Life
Project, January.

Bonikowski, Bart and Miller McPherson. 2006.
"Voluntary Associations." In Handbook of 21st
Century Sociology, edited by Dennis L. Peck and
Clifton Bryant. Thousand Oaks, CA: Sage.

Brewer, D. D. 1995. "The Social Structural Basis of
the Organization of Persons in Memory." Human
Nature 6:379^103.

Burt, Ronald S. 1984. "Network Items and the
General Social Survey." Social Networks
6:293-339.

. 1986. "A Note on Socio-metric Order in the

General Social Survey Data." Social Networks
8:149-74.

1997. "A Note on Social Capital and

Network Content." Social Networks 19:355-73.
Fischer, Claude S. 1982. To Dwell among Friends:

Personal Networks in Town and City. Chicago,

IL: University of Chicago Press.
. 2005 . "Bowling Alone: What's the score?"

Social Networks 27: 155-67.
Freeman, L. C, A. K. Romney, and S. C. Freeman.

1987. "Cognitive Structure and Informant

Accuracy." American Anthropologist 89:311-25.
Gershuny, Jonathan. 2003. "Web Use and Net Nerds:

A Neofunctionalist Analysis of the Impact of

Information Technology in the Home." Social

Forces 82:141-68.
Granovetter, Mark. 1973. "The Strength of Weak

Ties." American Journal of Sociology 78: 1360-80.
Hill, R. A. and R. I. M. Dunbar. 2003. "Social

Network Size in Humans." Human Nature

Beggs. 2000. "Core Networks and Tie Activation:

What Kinds of Routine Networks Allocate

Resources in Nonroutine Situations?" American

Sociological Review 65:598-618.
Jacobs, Jerry A. and Kathleen Gerson. 2001.

"Overworked Individuals or Overworked

Families." Work and Occupations 28:40-63.
Kogovsek, Tina and Anuska Ferligoj. 2004. "The

Quality of Measurement of Personal Support

Subnetworks." Qualify and Quantity 38:517-32.
Lin, Nan. 2001. Social Capitol: A Theory of Social

Structure and Action. New York: Cambridge

University Press.
Marin, A. 2004. "Are Respondents More Likely to

List Alters with Certain Characteristics?

Implications for Name Generator Data." Social

Networks 26:289-307 .
Marsden, Peter V 1987. "Core Discussion Networks

of Americans." American Sociological Review

52:122-31.
. 2005. "Recent Developments in Network

Measurement." Pp. 8-30 in Models and Methods

in Social Network Analysis, edited by Peter J.

Carrington, John Scott, and Stanley Wasserman.

New York: Cambridge University Press.
McPherson, Miller. 1983. "An Ecology of

Affiliation." American Sociological Review

48:519-32.
. 2004. "A Blau Space Primer:

Prolegomenon to an Ecology of Affiliation."

Industrial and Corporate Change 13: 263-80.
McPherson, Miller, Pamela A. Popielarz, and Sonja

Drobnic. 1992. "Social Networks and

Organizational Dynamics." American Sociological

Review 57:153-70.
McPherson, Miller and James Ranger-Moore. 1991.

"Evolution on a Dancing Landscape: Organizations

and Networks in Dynamic Blau Space." Social

Forces 10:19^X2.
McPherson, Miller and Lynn Smith-Lovin. 1981.

"Women and Weak Ties: Sex Differences in the

Size of Voluntary Associations." American Journal

of Sociology 87:883-904.
McPherson, Miller, Lynn Smith-Lovin, and James M.

Cook. 2001. "Birds of a Feather: Homophily in

Social Networks." Annual Review of Sociologv

27:415^14.
Moore, Gwen. 1990. "Structural Determinants of

Men's and Women's Personal Networks." American

Sociological Review 55:726—35.

SOCIAL ISOLATION IN AMERICA 375

Paxton, Pamela. 1999. "Is Social Capital Declining

in the United States? A Multiple Indicator

Assessment." American Journal of Sociology

105:88-127.
Putnam, Robert D. 1 995 . "Bowling Alone : America's

Declining Social Capital." Journal of Democracy

6:65-78.
. 2000. Bowling Alone: The Collapse and

Revival of American Community. New York: Simon

and Schuster.
Rotolo, Thomas. 1999. "Trends in Voluntary

Association Participation." Nonprofit and Voluntary

Sector Quarterly 28:199-212.
Rotolo, Thomas and John Wilson. 2004. "What

Happened to the 'Long Civic Generation'?

Explaining Cohort Differences in Volunteerism."

Social Forces 82 : 1 09 1 - 1 2 1 .
Ruan, Danching. 1998. "The Content of the General

Social Survey Discussion Networks: An

Exploration of the General Social Survey

Discussion Name Generator in a Chinese Context."

Social Networks 20:247-64.
Sampson, Robert J. 2004. "Neighborhood and

Community: Collective Efficacy and Community

Safety." New Economy 1 1 : 106-13.
Sampson, Robert J. and John H. Laub. 1990. "Crime

and Deviance over the Life Course: The Salience

of Adult Social Bonds." American Sociological

Review 55:609-27 .
Sampson, Robert J., Doug McAdam, Heather

Maclndoe, and Simon Weffer-Elizondo. 2005.

"Civil Society Reconsidered: The Durable Nature

and Community Structure of Collective Civic
Action." American Journal of Sociology.
111:673-714.

Smith, Tom W 1989. "Thoughts on the Nature of
Context Effects." Methodological Report No. 66,
National Opinion Research Center, September,
Chicago, IL.

Smith-Lovin, Lynn and Miller McPherson. 1993.
"You Are Who You Know: A Network Perspective
on Gender." Pp. 223-51 in Theory on
Gender/Feminism on Theory, edited by Paula
England. New York: Aldine.

Straits, Bruce C. 2000. "Ego's Important Discussants
or Significant People: An Experiment in Varying
the Wording of Personal Network Name
Generators." Social Networks 22: 123^40.

Verbrugge, L. M. 1977. "The Structure of Adult
Friendship Choices." Social Forces 56:576-97.

Wellman, Barry. 1979. "The Community Question:
The Intimate Networks of East Yorkers." American
Journal of Sociology 84: 120 1-3 1 .

Wellman, Barry, Bernie Hogan, Kristen Berg, Jeffery
Boase, Juan-Antonio Carrasco, Rochelle Cote,
Jennifer Kayahara, Tracy L.M. Kennedy and Phuoc
Tran. 2006. "Connected Lives: The Project." In
Networked Neighborhoods, edited by Patrick
Purcell. London: Springer.

Wellman, Barry and Scot Wortley. 1990. "Different
Strokes from Different Folks: Community Ties
and Social Support." American Journal of
Sociology 96:558-88.

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