Social Networks

views updated May 23 2018


Social networks—structures of relationships linking social actors—are omnipresent in contemporary society. People often obtain information about such things as job opportunities, housing, and medical care through interpersonal contacts rather than from formal sources such as the mass media. Networks provide emotional support in times of crisis as well as instrumental aid such as help with household tasks. Identities are constituted by locations in networks; opinions are formed and decisions are made in light of information and conformity pressures that flow through network linkages. Also, social networks are important channels through which both infectious diseases and innovations are diffused.

Ties among individuals in social networks give rise to important larger-scale social patterns. Levels of socioeconomic or ethnoreligious segregation in a society, for example, reflect the degree to which social ties such as marriage and friendship are confined to sets of persons with a common social status or heritage. Such characteristics become salient as markers of differentiation to the degree that they serve as bases for the formation of intimate social relationships. Networks that link individuals to supraindividual units such as work organizations and voluntary associations may serve as modes of integration or separation. Thus, the study of networks contributes to the linking of micro and macro levels of analysis in sociology.

Many macro-level social phenomena can be understood as networks. Increasingly, systems of production for goods (such as automobiles) and services (such as care for the severely mentally ill) are located in multiorganizational fields consisting of separate but interdependent units linked by contingent cooperation rather than in self-contained units administered through elaborate formalized sets of rules. Innovations in corporate strategy and governance diffuse through overlapping boards of directors and other interorganizational structures. Patterns of consensus and cleavage in community and national politics are shaped by alliances and conflicts in networks of governmental agencies, interest groups, and party organizations. In international relations, network ties among nation-states and international organizations define geopolitical alignments.

Emphasis on social networks grew as a result of substantive observations about contemporary society. Many early twentieth-century observers posited that large-scale transformations associated with industrialization—especially urbanization, bureaucratization, and the development of mass media—led to a "mass society" of atomized individuals in which formal, special-purpose ties supplanted diffuse interpersonal relations.

Several lines of research, however, pointed to the continuing vitality of social ties. Industrial sociologists found that informal structures were crucial to the day-to-day functioning of work organization. Indeed, workplace social networks came to be seen as a solution to the inflexibility and excess formalization of bureaucracies and as important incentives for (or impediments to) the performance of individual employees. Urban sociologists found that friendship, neighboring, and informal assistance remained prominent in large cities, although technological innovations in transportation and communication reduced the extent to which the formation and maintenance of those social ties were constrained by spatial considerations. Rural-to-urban and international migrants were not rootless citizens in a normless society but tended to settle in districts populated by persons from their places of origin. In contrast to the expectations of theories predicting protest and activism among those marginal and peripheral to society, researchers found that those active in social movements tended to be drawn from among the persons best integrated into communities, and social ties proved to be important channels through which new members were recruited to social movements.

A social network perspective highlights the interdependence among social actors. This extends beyond the competitive interdependence of actors competing for shares of a stock of scarce resources to encompass obligations and commitments that accumulate as a result of past social interaction. Individual action is embedded in, and therefore continually affected by, preexisting ties between specific actors (Granovetter 1985). In some theories, individuals are viewed as largely passive recipients of environmental pressure; in this structural emphasis, social networks constitute constraints that limit an actor's discretion. An alternative view makes more room for individual agency, viewing networks as structures of opportunity or social resources. Assuming a context of constrained voluntarism, it treats individuals as proactive, self-interested agents who use networks to manipulate outcomes to their advantage (Haines 1988; Emirbayer and Goodwin 1994).

Social scientists have used the term "social network" metaphorically for some time. Beginning in the 1970s, however, scholarly attention to the analytic development of the social network approach increased. It is now seen as a distinct specialty within several social science disciplines, especially sociology and anthropology, and has many adherents in professional schools, particularly those of business administration and public health. Mathematicians and statisticians have participated in this work, especially the development of novel techniques for studying relations between interdependent social units. These methods are distinct from the conventional ones used to study relations between variables within presumably autonomous units. The theoretical assumptions of formal network models are often implicit (Granovetter 1979), and a distinct "network theory" has not developed. Contemporary studies of social networks instead draw on diverse sociological and social psychological theories.


Some foundations of a methodology for studying networks of social relations were laid in Moreno's Who Shall Survive? (1934). Moreno coined the term "sociometry" to refer to methods for describing group structures and individual positions within them. His work focused on the affinities and disaffinities of individuals for one another, and his "sociometric test" accordingly stressed affective choices and rejections. These network data were mapped in "sociograms" in which persons were located at different points, with lines indicating the connections between them. Such graphic representations are also common in contemporary network analysis (Figure 1). On the basis of their locations in sociometric networks of affect, individuals were classified as attractive, isolated, rejected, and so forth.

Jennings collaborated with Moreno in developing sociometric methods; her (1943) work reported studies of attractiveness and emotional expansiveness. Sociometry as practiced by Moreno and Jennings had an applied component: They attempted to use sociometric measurements as a basis for rearranging groups to enhance both group functioning and individual creativity.

Displays such as sociograms are extremely useful as visualization devices but do not facilitate formal analysis. Forsyth and Katz (1946) and Luce and Perry (1949) were among the first to attempt to surmount the limitations of sociograms by representing networks in the form of matrices. They argued that this would reduce the subjectivity of statements about sociometric structure and allow objective identification of chains, groups, and cliques in network data. In later studies, the application of graph theory (Harary et al. 1965) to the analysis of networks has extended those early efforts.

A second set of influences on the development of social network analyses has emanated from the fieldwork of social anthropologists in complex societies. Those analysts observed that the categorical concepts of a structural-functional approach were insufficient for the study of societies in which not all behavior was regulated by "corporate groups"—institutions of kinship, community, or work. Barnes (1954) is credited with the first use of the term "social network" to refer to a set of existing social relationships as distinct from cultural prescriptions about the construction of such ties. In its initial formulations, the concept was used to refer to informal or extrainstitutional links, but it was soon noted that formalized relations and groups also could be analyzed as networks of interactions.

Classic studies in the anthropological tradition display the same variability in theoretical orientations seen in present-day work: Bott (1957) treated social networks as sources of norms prescribing an appropriate allocation of tasks between spouses, while Boissevain (1974) stressed the potential use of networks by maneuvering, self-interested entrepreneurs.


Social networks are studied from many standpoints, including the sociocentric and egocentric perspectives. Researchers with a sociocentric orientation examine complete networks of actors and relations, studying the global properties of a network and characterizing the position of any given actor by reference to all the others. Egocentric network analysis takes the perspective of individual actors and the "personal networks" surrounding them, focusing on the local structure of each actor's interpersonal environment.

Figure 1 depicts a complete network with fourteen actors, with each one represented as a circle or square. Lines connecting those points indicate relationships between pairs of actors, such as communication ties and expressions of affect. An actor's "first-order" egocentric network consists of the other actors to which it is linked and the relationships among them; actor G's egocentric network includes C, D, and F, while that of H consists of B, L, and N. The "second-order" zone of a focal actor's egocentric network includes those to which the actor is linked via one intermediary; the second-order zone of G's network consists of actor A, while that of H includes both A and I.

Arrows indicate directionality; for example, actors A and E are involved in a reciprocal relationship, while A and C are linked by an asymmetric tie in which the relationship flows in only one direction. Indirect relationships join actors to one another through intermediaries: for instance, H and I are indirectly linked through B.

The density of a network reflects the overall intensity of connectedness among actors. In Figure 1, sixteen of the ninety-one distinct pairs of actors have direct relationships, and so the network has a density of 18 percent. There are, however, wide variations in the density of the egocentric networks surrounding actors: G is in a very dense or closely knit locality, while H is in a sparse or loosely knit region.

Diagrams of more complicated networks might use lines of different thicknesses to represent relationships of varying intensity or different types of lines to show distinct relationships, such as providing emotional support versus giving instrumental aid. Different types of actors can be represented by different symbols; the actors in circles in Figure 1 might be men, while those in squares might be women. When a relationship typically joins actors that have the same attributes or statuses, as in Figure 1, it is said to display homophily.

Social ties, especially those involving positive sentiment, often create transitive configurations. In Figure 1, for example, transitivity implies that by virtue of the links between C and D and between C and F, there will also be a tie between D and F. Strong tendencies toward transitivity create closure and tend to fragment a group into distinct cliques: The mutually interconnected set of four actors (C, D, F, and G) provides an illustration. Relationships that do not conform to the transitivity principle are important sources of integration between otherwise separate parts of a social structure (Granovetter 1973): in Figure 1, the I–B and A–B ties exemplify bridges of this kind.

Actors may be central in a network because they are involved in many relationships, are in a controlling position between other pairs of actors, or are comparatively close to others (Freeman 1979). Sociometry referred to central actors as "sociometric stars." In Figure 1, actors A and B occupy relatively central locations. Those such as E, J, and L are peripheral within the network. Actor M is not involved in any relationships and is said to be an isolate.

Two actors are said to occupy the same position in a social network when they have profiles of relationships to other actors that are identical in a particular way (Borgatti and Everett 1992); these actors are therefore substitutable for each other from an observer's standpoint. Two actors having the same relationships to the same others are structurally equivalent. In Figure 1, actors J and K both have a reciprocal relationship with actor I but no direct relationship with each other or any of the other actors. J and K are thus structurally equivalent, as are three other pairs: C and D, F and G, and L and N. Actors are said to be role-equivalent when they have the same types of relationships to the same types of other actors. Actors L and K are role-equivalent, but not structurally equivalent; although they occupy similarly peripheral locations in the system of relations, L's direct link is to H, while K's is to I.

Additional patterns often appear in networks that involve more than one type of social relationship. Exchange patterns arise when a flow of one type in one direction is directly or indirectly reciprocated by a flow of a second type. A multiplex pattern occurs when the relationship between two actors consists of two or more distinct strands, such as kinship and emotional support; a uniplex relationship has only one strand.

Concepts and methods for identifying subgroups within networks have drawn much attention. The two dominant approaches focus on cohesion and equivalence as grouping principles. Techniques that emphasize cohesion locate subsets of densely interconnected actors; fully connected cliques are a limiting case. Blockmodel analysis (White et al. 1976) and related positional methods group equivalent actors together. This yields considerable flexibility. Social positions can be defined by the common ties of actors to outsiders rather than by actors' links to one another; for example, those in "broker" roles occupy mediating locations between other positions but are not necessarily linked to other brokers. Moreover, positional approaches are not confined to a single type of tie; they can identify subgroups on the basis of patterns in multistranded relations rather than focusing on a single type of tie extracted from its context, as approaches resting on cohesion generally must. Thus, positional analyses of international trade relations may examine flows of raw materials and flows of processed goods simultaneously.


Rational choice explanations of the formation of network ties are based on exchange theory: Social relations form when actors depend on one another for resources. Related behaviorist accounts stress a reinforcement history. An exemplar is Blau's (1955) description of the exchange of advice for expressions of deference among coworkers in a bureaucracy. The terms of exchange and thus the relative power of the actors involved depend on the number of alternative actors who control different resources, the extent of unity among those with a given resource, and the parties' relative interests in outcomes controlled by others (Cook 1982; Burt 1980).

Exchange-theoretic reasoning provides a basis for some commonly observed micro-level network patterns. To maintain autonomy and avoid power disadvantages, actors should avoid asymmetric relations in favor of reciprocal ones. Multiplex ties in which relations of solidarity overlie instrumental exchange links can protect people against exploitation by actors in positions of power. These ideas have played an important role in resource dependence theories of interorganizational relations. Such theories suggest, for example, that interdependent organizations tend to form network ties such as long-term contracts, joint ventures, interlocking directors, and mergers (Pfeffer 1987).

Some attempts to explain tendencies toward homophily are preference-driven accounts in which people actively seek out similar associates. From this viewpoint, communication is easier if people share implicit premises regarding interaction and trustworthiness in the face of uncertainty is enhanced if partners can assume that they have shared interests and predispositions.

Other lines of theorizing about the sources of homophily stress the structure of opportunities for association. Feld (1981) observes that most relationships arise within "foci" of association such as families, neighborhoods, workplaces, and voluntary associations. When segregating processes create foci composed of persons with similar attributes, they create systematic biases toward homophily. Blau's macrosociological theory (Blau and Schwartz 1984) postulates that networks vary with opportunities for association. Blau shows, without any assumptions about preferences, that intergroup relations—the converse of homophilous ones—are more likely for small than for large groups, when there is great inequality or heterogeneity in a population instead of little, and when different characteristics (e.g., socioeconomic status, race, ethnicity) that structure the formation of social ties are intersecting (or uncorrelated) rather than consolidated. The implications of these factors for intergroup relations depend on the degree to which they penetrate into substructures such as Feld's foci: Distributional effects on intergroup association are strongest when heterogeneity, inequality, and intersection lie within rather than between substructures.

Transitivity has been most intensively studied for relations of positive sentiment; there the theoretical case for it rests on balance theories that posit pressures toward cognitive consistency (Davis and Leinhardt 1972). Tendencies toward closure also may result from increased opportunities for contact resulting from the copresence of actors in a triad, or an actor in contact with two others may facilitate or serve as a guarantor for a venture involving the other two. Principles of expectation states theory predict transitivity in dominance relations (Fararo and Skvoretz 1986).


A network perspective lends itself to the construction of theories at multiple levels. Contextual theories that examine the effects of an actor's position in a network on achievement, well-being, and other individual-level outcomes are common, and extensive research literatures have developed around some of them. Network entrepreneurship, diffusion and influence, social support, and power are among the most prominent themes in such works. Group-level theorizing about the properties of complete networks is less typical, although there have been important efforts in this direction. As Coleman (1990) stresses, group-level theorizing is a demanding enterprise.

Granovetter's (1973) discussion of "weak ties" has been a fruitful source of ideas for network analysts. Although Granovetter defines tie strength in terms of dyadic content (intimacy, intensity, exchange of services and time commitments), the "strength of weak ties" arises from their location within a network structure. Weak ties are less subject than strong ones to the transitivity pressures that induce closure and thus are more likely to be bridges that join distinct subgroups, thereby serving as channels for integration and diffusion. Different contextual theories positing network effects may stress the virtues of either strong or weak ties.

The purposive use of networks as individual-level "social capital" is a prominent theme in writing about network effects. Much research has been done on how networks facilitate or impede instrumental actions, particularly job seeking. Granovetter (1995) stressed the informational advantages of wide-ranging networks composed of many weak ties. He reasoned that such networks are likely to connect actors to diverse information sources that provide novel information and access to powerful others; by contrast, persons in a densely connected clique are apt to have similar social standing and know similar things. Other writing in this vein emphasizes the content rather than the form of networks. Lin (1990) contends that networks composed of highly ranked contacts are the most advantageous to an actor. Weak ties may facilitate access to social resources, but the aid such contacts can provide reflects their power and influence rather than the type of channel that links them to the actor.

Burt (1992), developed influential ideas about network entrepreneurship. Like Granovetter, Burt stressed the benefits of loosely knit networks for obtaining information quickly. Structural holes refer to the absence of connections between an actor's contacts in a sparse network; thus, in Figure 1 there are holes separating actor B's contacts (A, I, and H). Beyond providing actors with the ability to acquire information sooner than competitors can, Burt argues that networks rich in structural holes confer control benefits. Actors at the middle of networks that bridge many holes gain autonomy and leverage over others by virtue of their unique interstitial positions. They are able to place their contacts in competition with one another, avoid excessive dependence, and negotiate favorable bargains. Empirical applications in diverse settings lend support to these ideas: Structural holes have proved advantageous in studies of competition for promotions and bonuses in firms and studies of comparative profit margins in manufacturing industries.

Studies of the role of networks in diffusion and influence processes echo debates over cohesion and equivalence as bases for defining network subgroups (Marsden and Friedkin 1993). This work posits that networks provide actors with a basis for constructing reference groups and social comparisons (Erickson 1988). Approaches that stress the socializing potential of cohesive ties contend that people look to close associates for guidance toward appropriate attitudes or conduct in conditions of uncertainty. Network closure thus is viewed as a source of locally defined norms, as persons in dense networks respond to consistent conformity pressures from their strong ties.

Burt (1987) suggests an important alternative process of diffusion or influence, arguing that in seeking normative direction, actors look not to their close contacts but to their competitors. They engage in a process of role taking, examining the views held or the actions taken by structural peers who occupy similar positions within a system of relations. Conformity to norms here is less a matter of social pressure from the environment than the result of an actor's mimicry of others (DiMaggio and Powell 1983).

An extensive research literature on the sociology of health and illness draws a connection between social networks, exposure to stressors, the availability of social support, and well-being (House et al. 1988; Thoits 1995). Social networks are "structural" elements that may facilitate access to supportive contacts but also may expose someone to additional stressors, conflicts, and demands; hence, the quality as well as the structure of ties within networks must be considered. A "direct effect" view states that receiving social support enhances health and well-being in all conditions. The "buffering hypothesis" suggests a conditional effect in which those with supportive networks have less severe responses to stressful life events.

Several mechanisms have been suggested to account for the way in which aspects of social networks translate into social support and measures of physical and mental well-being. Some of these suggestions have a Durkheimian emphasis, reasoning that people integrated into dense networks—that is, strongly tied to a number of partners who are strongly tied to each other—have better-defined social identities, stronger senses of internal control, and more positive self-evaluations, which in turn may lead to the use of more effective coping strategies under stress. Collins (1988) suggests that network density indicates that an individual is integrated into the "interaction rituals" of a solidary group, a situation that produces moral sentiments and energies that enhance well-being.

It is relatively well established that the availability of a strong tie or confidant has health-promoting effects (Thoits 1995). Theories stressing the availability of support resources imply that the size of a personal network is linked to physical and psychological health. Large, diverse networks are thought to facilitate adjustment to change. Contacts in one's network may offer companionship as well as both instrumental and emotional assistance; they can both provide health information and focus attention on it. Social contacts also may be sources of regulation and control, providing social feedback on one's behavior and performance, discouraging harmful behaviors such as substance abuse, and encouraging beneficial ones such as adherence to treatment protocols. It is increasingly recognized that providing social support can be burdensome and that stress as well as aid may emanate from relationships within social networks.

Network theorists have given substantial attention to the connection between an actor's location in a social network and social standing or prestige. Freeman's (1979) discussion of the conceptual foundations of centrality measures focused on processes in communication networks. He observed that distinct measures are sensitive to communication activity, the capacity to control the communications of others, and the capacity to avoid the controlling actions of others. Many empirical studies have documented an association between centrality and manifestations of power or influence.

Exchange-theoretic approaches observe that actors with predominantly favorable exchange ratios with others are central within networks of dependency relations and hence acquire power (Cook 1982). No universal principle leads to that connection, however; instead, it depends on a particular form of exchange. For Cook this is "positively connected" or "productive" exchange in which actors must combine diverse resources to be successful; hence, the use of one exchange relation tends to encourage the use of others, and advantages emerge for those in intermediary "broker" positions. Willer (1992) terms these "flow" networks. For Coleman (1990), the requisite conditions include resource transferability or fungibility: For systems of social exchange to develop fully, actors must be able to transfer not only control over resources but also the right to further transfer such control.

Under other conditions of exchange, network positions have different consequences for power. Among these are what Cook (1982) calls "negatively connected" exchange networks and Willer (1992) terms "restricted" exchange networks. In these networks, resources do not flow through positions and the use of one relation rules out or makes less likely the use of others. Matching systems such as marriage and dating markets exemplify negatively connected or restricted networks. In these conditions no special advantages accrue to an actor in a central position; instead, power is concentrated in actors who can exclude others from exchanges (Markovsky et al. 1988). The capacity to exclude others can depend both on the nuances of a network's structure and on the incentives or rules governing exchange in any given situation. Depending on such subtleties, there may be a nonlinear association between centrality and power; a network also may decompose into small substructures as some potential exchange relations fall into disuse.

Theorizing about network effects at the level of aggregates is less extensive than is that about networks as contexts for individual action. One line of work examines the implications of structural biases toward homophily or transitivity for the spread of diseases and innovations (Morris 1993). Another considers how the centralization or dispersion of networks shapes differences in system performance or effectiveness (Laumann and Knoke 1987). Still another deals with networks and collective action: Social density has been viewed as an infrastructure that allows latent "interest groups" to overcome social dilemmas (Marwell et al. 1988). Granovetter (1973) warns against excessive closure, however: Once formed, a coalition or "collective actor" may lack the social connections required for ultimate political success.

Some theorists have developed the notion of social capital as a collective rather than an individual property. Coleman (1990) suggests that closed social networks can create trust and enforce strong norms that facilitate collective action. Actors in densely interconnected systems can expect to encounter one another frequently in the future, and a reputation for trustworthiness therefore becomes valuable. Moreover, frequent communication among densely linked actors means that information about a failure to honor obligations diffuses quickly and that sanctions can be applied rapidly. Coleman asserts that strong norms of trust are essential to the creation of "social credit": aid or assistance contributed in exchange for future compensation. Preexisting social networks thus are valuable as sources of social capital to the extent that they are appropriable for new purposes.

Different varieties of network theory make contrasting observations about network density. Density can integrate an actor into a subculture, provide a well-defined social identity, create and enforce norms, and promote the production of collective goods it simultaneously may subject one to conformity pressures and limit the diversity of one's affiliations. Reconciling these seemingly conflicting effects of density represents a challenge in the contemporary study of networks. Understanding the manner in which networks channel and block transactions among the elements of society will remain a crucial and intriguing task for twenty-first-century sociology.


A number of review articles and collections treat aspects of network analysis in greater depth. Mitchell (1974) provides a useful review of the anthropological approach. Wellman (1983) reviews basic principles from a sociological perspective. Review articles on substantive applications appear in Wasserman and Galaskiewicz (1994). The journal Social Networks (1978–present), edited by Linton Freeman, presents methodological advances and substantive studies. Marsden (1990) surveys the literature on measurement, and Wasserman and Faust (1994) provide a comprehensive review of analytic methods.


Barnes, J. A. 1954 "Class and Committees in a Norwegian Island Parish." Human Relations 7:39–58.

Blau, Peter M. 1955 The Dynamics of Bureaucracy. Chicago: University of Chicago Press.

——, and Joseph E. Schwartz 1984 Crosscutting SocialCircles. New York: Academic Press.

Boissevain, Jeremy 1974 Friends of Friends. New York: St. Martin's.

Borgatti, Stephen P., and Martin G. Everett 1992 "Notions of Position in Social Network Analysis." In Peter V. Marsden, ed., Sociological Methodology 1992. Oxford, UK: Blackwell.

Bott, Elizabeth 1957 Family and Social Network London: Tavistock.

Burt, Ronald S. 1980 "Autonomy in a Social Topology." American Journal of Sociology 85:892–925.

—— 1987 "Social Contagion and Innovation: Cohesion versus Structural Equivalence." American Journal of Sociology 92:1287–1335.

—— 1992 Structural Holes: The Social Structure of Competition. Cambridge, Mass.: Harvard University Press.

Coleman, James S. 1990 Foundations of Social Theory. Cambridge, Mass.: Harvard University Press.

Collins, Randall 1988 Theoretical Sociology. New York: Harcourt Brace Jovanovich.

Cook, Karen S. 1982 "Network Structures from an Exchange Perspective." In Peter V. Marsden and Nan Lin, eds., Social Structure and Network Analysis. Beverly Hills, Calif.: Sage.

Davis, James A., and Samuel Leinhardt 1972 "The Structure of Positive Interpersonal Relations in Small Groups." In Joseph Berger, Morris Zelditch, Jr., and Bo Anderson, eds., Sociological Theories in Progress. Boston: Houghton Mifflin.

DiMaggio, Paul, and Walter W. Powell 1983 "The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields." American Sociological Review 48:147–160.

Emirbayer, Mustafa, and Jeff Goodwin 1994 "Network Analysis, Culture, and the Problem of Agency." American Journal of Sociology 99:1411–1454.

Erickson, Bonnie H. 1988 "The Relational Basis of Attitudes." In Barry Wellman and S. D. Berkowitz, eds., Social Structures. New York: Cambridge University Press.

Fararo, Thomas J., and John Skvoretz 1986 "E-State Structuralism: A Theoretical Method." American Sociological Review 51:591–602.

Feld, Scott L. 1981 "The Focused Organization of Social Ties." American Journal of Sociology 86:1015–1035.

Forsyth, Elaine, and Leo Katz 1946 "A Matrix Approach to the Analysis of Sociometric Data: Preliminary Report." Sociometry 9:340–347.

Freeman, Linton C. 1979 "Centrality in Social Networks I: Conceptual Clarification." Social Networks 1:215–239.

Granovetter, Mark S. 1973 "The Strength of Weak Ties." American Journal of Sociology 78:1360–1380.

—— 1979 "The Theory-Gap in Social Network Analysis." In Paul W. Holland and Samuel Leinhardt, eds., Perspectives on Social Network Research. New York: Academic Press.

—— 1985 "Economic Action and Social Structure: The Problem of Embeddedness." American Journal ofSociology 91:481–510.

—— 1995 Getting a Job: A Study of Contacts and Careers, 2d ed. Chicago: University of Chicago Press.

Haines, Valerie A. 1988 "Social Network Analysis, Structuration Theory and the Holism-Individualism Debate." Social Networks 10:157–182.

Harary, Frank, Robert Z. Norman, and Dorwin C. Cartwright 1965 Structural Models: An Introduction tothe Theory of Directed Graphs. New York: Wiley.

House, J. S., D. Umberson, and K. R. Landis 1988 "Structures and Processes of Social Support." Annual Review of Sociology 14:293–318.

Jennings, Helen Hall 1943 Leadership and Isolation. New York: Longmans, Green.

Laumann, Edward O., and David Knoke 1987 The Organizational State. Madison: University of Wisconsin Press.

Lin, Nan 1990 "Social Resources and Social Mobility." In Ronald L. Breiger, ed., Social Mobility and SocialStructure. New York: Cambridge University Press.

Luce, R. Duncan, and Albert D. Perry 1949 "A Method of Matrix Analysis of Group Structure." Psychometrika 14:95–116.

Markovsky, Barry, David Willer, and Travis Patton 1988 "Power Relations in Exchange Networks." AmericanSociological Review 53:220–236.

Marsden, Peter V. 1990 "Network Data and Measurement." Annual Review of Sociology 16:435–463.

——, and Noah E. Friedkin 1993 "Network Studies of Social Influence." Sociological Methods and Research 22:127–151.

Marwell, Gerald, Pamela E. Oliver, and Ralph Prahl 1988 "Social Networks and Collective Action: A Theory of the Critical Mass III." American Journal ofSociology 94:502–534.

Mitchell, J. Clyde 1974 "Social Networks." Annual Review of Anthropology 3:279–299.

Moreno, J. L. 1934 Who Shall Survive? Washington, D.C.: Nervous and Mental Disease Publishing.

Morris, Martina 1993 "Epidemiology and Social Networks: Modeling Structured Diffusion." SociologicalMethods and Research 22:99–126.

Pfeffer, Jeffrey 1987 "A Resource Dependence Perspective on Intercorporate Relations." In Mark S. Mizruchi and Michael Schwartz, eds., Intercorporate Relations. New York: Cambridge University Press.

Thoits, Peggy A. 1995 "Stress, Coping, and Social Support Processes: Where Are We? What Next?" Journalof Health and Social Behavior, extra issue, pp. 53–79.

Wasserman, Stanley, and Katherine Faust 1994 SocialNetwork Analysis: Methods and Applications. New York: Cambridge University Press.

——, and Joseph Galaskiewicz, eds. 1994 Advances inSocial Network Analysis: Research in the Social andBehavioral Sciences. Thousand Oaks, Calif.: Sage.

Wellman, Barry 1983 "Network Analysis: Some Basic Principles." Sociological Theory 1:155–199.

White, Harrison C., Scott A. Boorman, and Ronald L. Breiger 1976 "Social Structure from Multiple Networks I: Blockmodels of Roles and Positions." American Journal of Sociology 81:730–780.

Willer, David 1992 "Predicting Power in Exchange Networks." Social Networks 14:187–211.

Peter V. Marsden

Social Networks

views updated Jun 08 2018

Social Networks

Married couples and families do not exist in isolation, but are embedded in a network of social relationships and culture. Even prior to marriage, relations with family members, friends, and acquaintances can influence dating activities and romantic relationships. When individuals become a couple, they must deal with the demands of both their own social ties and those of their spouses. Couples informally negotiate the degree to which they will maintain separate friendships, balance their own and their partner's family relationships, and engage in social activities as a couple. Relationships with marital partners, friends, and families change as individuals and couples age. It is increasingly clear that social relationships help to shape the basic nature of married life. In examining social relationships, some researchers use the terms social network and social support interchangeably (Schonauer et al. 1999).

Defining Social Networks

Personal social networks are typically defined as "a collection of individuals who know and interact with a particular target individual or couple" (Milardo 1988, p. 20). Researchers can assess the structural characteristics of an individual's network such as network size, role composition (the number of individuals, including family, friends, or work associates, in the network), or network density (interconnectedness among members). Content characteristics of networks describe the nature of linkages between the individual and network members such as relationship satisfaction, feelings of closeness, or reciprocity. Functional characteristics of networks describe linkages in which a given person serves some function for the focal individual, such as providing social support or informal help (Laireiter and Baumann 1992).

The social networks of couples have been investigated in three major ways. Using an individual perspective, researchers have defined a couple's social ties in terms of the separate personal networks maintained by each partner. At the dyadic level, a couple's network has been viewed as those network members jointly shared by the couple. A configural approach conceptualizes a couple's network as a composite of the shared and separate ties contributed by both partners. Individual, dyadic, and configural perspectives differ in their assumptions about the role of network structure for couples, and each perspective has certain advantages and limitations (Stein et al. 1992).

There is no one correct definition of a social network, but rather different network delineation strategies yield different data about social relationships. In studying the social context of marital and family life, researchers distinguish between the structure, content, and function of social network relationships. Researchers who study married couples must also decide if they are interested in the separate networks of marital partners, the degree of overlap between the partners' social ties, or some composite picture of the couple's network relations.

Social Network Structure: Relationship Opportunities and Constraints

The structure of social networks is critical for understanding opportunities and constraints in the development and maintenance of social relationships. Friends and family can introduce an individual to others who may have the potential for friendship or romantic involvement. Existing network ties can also limit opportunities to form new relationships, given that a person has only a finite amount of time and energy to engage in social relationships. Researchers typically acknowledge the reciprocal influence of married couples and their social networks—namely, that network ties influence the development and maintenance of a couple's relationships and that being "a married couple" affects the nature of their social network ties.

Some individuals withdraw from network relationships as they become romantically involved, but network withdrawal is probably not a universal phenomenon. Instead, different types of networks (e.g., interactive versus close associates) and different network sectors (e.g., family, close friends, peripheral friends) undergo various changes as partners become more involved in a dating relationship ( Johnson and Leslie 1982). For example, to assess the interactive networks of college-age dating couples, Robert Milardo, Michael Johnson, and Ted Huston (1983) had respondents keep daily logs for two ten-day periods separated by a ninety-five–day span. Respondents in later stages of couple involvement reported that they interacted with fewer total network members than respondents in earlier stages of involvement. However, longitudinal data results found no significant differences in total network size between respondents whose dating relationships had become more involved and respondents whose dating relationships had deteriorated. In fact, there was an increase in the number of family members and of intermediate friends in the network of dating couples who increased in romantic involvement.

As couples become increasingly interdependent in their personal lives, they develop increasingly interdependent social networks (Milardo 1982). Studies investigating couples' networks have assessed the degree of overlap between network members listed by both husbands and wives. Shared networks of family were found to be a particularly valuable source of support (Veiel et al. 1991). However, husbands and wives in the study rarely shared the same network member as their closest confidant. These findings suggest the importance of both individual and shared network ties as supportive resources for married couples.

Catherine Stein and her colleagues (1992) found that couples with different types of networks reported significantly different levels of marital satisfaction and individual well-being. For example, couples whose conjoint networks featured a relatively large number of friends for both husbands and wives also reported significantly higher levels of marital satisfaction than couples in some of the other network types. However, husbands reported significantly higher levels of depression than wives in this type of network. Postulating a direct relationship between separate friendships and individual well-being would suggest that friends might help wives with feelings of depression in a way that men's separate friendships do not. Such findings suggest that conjoint network structure may have different implications for the marital relationship and the psychological wellbeing of individual partners.

Gender Differences in Social Networks

Developing and maintaining network ties requires a set of interpersonal skills and the desire and opportunity to use those skills. Men and women often differ in the nature of their interpersonal exchanges and in their opportunities for social inter-action (Dykstra 1990). Research indicates that men and women structure their personal networks differently and that networks may serve different functions for husbands and wives. For example, wives generally report larger networks of kin and greater network interconnectedness than husbands (Antonucci and Akiyama 1987).

Claude Fischer and Stacey Oliker (1983) suggest that age and lifestyle stage account for network differences, with young married men having larger networks than their wives, and the reverse being true for older married couples. Studies of middle-aged and older adults indicate that married men are more likely to report their wives as their primary confidants and sources of support, whereas women are more likely to report confidants other than their husbands and to rely on friends and children as sources of support (Antonucci and Akiyama 1987). Women are more likely than men to request assistance from network members in general (Butler, Giodano, and Neren 1985).

Network composition may affect women's opportunities for social contact outside of the home, such as participation in the labor force. Although a number of factors influence work force participation, social network connections can play a critical role in finding and securing paid employment. As women's networks tend to have larger proportions of kin compared to their male counterparts, the networks of women may lack the heterogeneity of members needed to provide unique information and help in finding a job (Wellman and Wortley 1990). Research has shown that women who have large, diverse social networks are more likely to be working for pay as compared with women whose networks are less diverse (Stoloff, Glanville, and Bienenstock 1999).

Cultural Differences in Social Networks

Ethnicity, race, and culture have also been shown to shape social network ties. Network characteristics such as network size, composition, frequency of contact, and interconnectedness among members have been found to differ for people from different ethnic, racial, and cultural backgrounds. However, overall research findings in this area tend to be inconsistent. Recent studies compare the social networks of minority populations with those of Caucasians with little attention given to comparisons across a variety of ethnic or cultural groups.

In his overview of the features of social networks of people in the United States, Peter Mardsen (1987) found that whites had the largest networks, Hispanics had intermediate-sized networks, and African Americans had the smallest networks. This study also found that African Americans had a smaller proportion of kin and less gender diversity in their networks than white respondents.

Other studies support the findings that African-American social networks tend to be smaller than those of whites or other non-European groups (Pugliesi and Shook 1998). However, some research has shown that African Americans have more kin members in their networks and that their networks often include members from church and religious communities (Ajrouch, Antonucci, and Janevic 2001; Kim and McKenry 1998; Roschelle 1997). It may be that differences in assessing social network ties account for some of the inconsistent findings.

There is evidence to suggest that Hispanics have highly interconnected networks that include kin and friends and have strong church and school ties (Wilkinson 1993). For example, Thomas Schweizer and his colleagues (1998) found that both Euro-American and Hispanic participants had networks that were homogenous with regard to ethnicity. In addition, when compared to Euro-American networks, the networks of Hispanic participants were dominated by family ties, with most kin members living in the same neighborhood.

Relationship Processes in Social Networks

Family theories such as the Double ABCX Model (McCubbin and Patterson 1983) underscore the importance of social networks in helping individuals cope with family crises. Network relationships are not only important sources of support in times of stress, but the nature of family crises may themselves necessitate changes in the structure and quality of network ties. For example, social network members provide emotional and instrumental support during times of bereavement following the death of a family member (Suitor and Pillemer 2000). Structural characteristics, such as network composition and the interconnectedness among network members, are thought to play a role in mourning and adjustment to the death of a spouse (Blackburn, Greenburg, and Boss 1987).

How do networks of family and friends shape the nature of relationships between couples and families? Couples and families typically have regular and frequent contact with relatives and friends. Friends and relatives provide couples and individual partners with both emotional support and a variety of different kinds of tangible assistance (Stein and Rappaport 1986). However, there may be some negative outcomes when couples use their networks to help them deal with marital distress.

Danielle Julien and Howard Markman (1991) examined associations among spouses' problems, the support partners sought within and outside of marriage, and levels of individual and marital adjustment. Husbands' support was a particularly relevant component of wives' marital satisfaction, and marital distress was associated with less mobilization of spouses' support. Mobilization of support from network members was associated with greater marital distress. Discussing marital problems with outsiders was associated with low marital adjustment. The authors speculated that network members may provide alternative resources, reducing spouses' motivation to address each other to solve personal problems.

Contact with close network ties can also lead to social comparisons about the nature of relationships and marriage. People can use information and observations of other couples or individual partners to evaluate their own feelings, behaviors, and expectations for couples and marital relations. Social comparisons can provide information about the equity of one's relationship relative to others, validate the correctness of one's attributions or expectations, or reduce uncertainty.

In an exploratory study, Sandra Titus (1980) found that more than half of the thirty married couples in her sample reported explicitly comparing their own marriage with friends' marriages during interactions with friends or their spouses. Social comparisons were more common in younger couples with children less than five years of age and more common among wives than husbands. Social comparisons seemed to establish a frame of reference for marital expectations, helped couples identify issues to discuss in their own marriages, and helped couples to evaluate or affirm the quality of their marriages.

Renate Klein and Robert Milardo (2000) examined the role that network members play in couples' perceptions of how they manage relationship conflict. After identifying one controversial issue in their relationship, partners were independently asked to delineate their social networks in terms of members who they thought would approve of their point of view (supporters) and those who would disapprove of their position (critics). The number of perceived supporters identified by respondents was positively related to their belief that their position in the conflict was legitimate, justified, and reasonable (self-legitimacy). The number of perceived critics was related to a decreased sense of self-legitimacy for men, but not for women. These preliminary findings suggest that the social comparison process may be different for men and women as they manage relationship conflict. It may be that men's sense of legitimacy in relationship conflict is related to a lack of network critics, whereas women's feelings of conflict legitimacy are related to having supporters to validate their point of view.

Social Networks and Aging

Changes in social networks as a function of the aging process have been the focus of research. There is evidence to suggest that as people age, their social networks tend to grow smaller and are composed largely of kin (Lang 2000; Sluzki 2000). As individuals age and view their future as time-limited, they are likely to seek relationships that provide the most emotional impact and short-term benefits and discontinue those relationships that are less satisfying (Carstensen, Isaacowitz, and Charles 1999). Thus, the motivation to seek and maintain social contacts is thought to be linked to an individual's perceptions of their future.

The gerontological literature documents the importance of families, particularly adult daughters, in caring for elders (see Dwyer and Coward 1992). However, as more couples in the United States choose not to have children, the family members available for support and care become more limited. In a study by Melanie Gironda, James Lubben, and Kathryn Atchison (1999), elders without children generally reported less contact with other relatives and family members than those elders with children. It appears that elders without children may renew old friendships or relations with distant kin in later life if geographic location permits (Sluzki 2000). Thus, the social networks of some elders may largely consist of recycled or renewed relationships with people who share a long personal history, if not an extended period of sustained interaction.


Social network analysis has helped researchers to more systematically describe different kinds of social relationships that exist and develop within the context of marriage and family life. Yet, researchers are only beginning to examine the complex, reciprocal influence of network forces on family relationships and marital ties. More methodological and conceptual work is needed to understand the network conditions that best help to nurture and support the many aspects of marriage and the family.

See also:Communication: Couple Relationships; Dating; Elders; Family Roles; Fictive Kinship; Friendship; Infidelity; Marital Quality; Neighborhood; Relationship Dissolution; Relationship Initiation; Relationship Maintenance; Renewal of Wedding Vows; Singles/Never Married Persons; Stress


ajrouch, k. j.; antonucci, t. c.; and janevic, m. r. (2001). "social networks among blacks and whites: the interaction between race and age." journal of gerontology 56b:s112–s118.

antonucci, t. c., and akiyama, h. (1987). "an examination of sex differences in social support among older men and women." sex roles 17:737–749.

blackburn, j. a.; greenburg, j. s.; and boss, p. g. (1987)."coping with normative stress from loss and change: a longitudinal study of rural widows." journal of gerontological social work 11:59–70.

butler, t.; giodano, s.; and neren, s. (1985). "gender andsex-role attributions as predictors of utilization of natural support systems during personal stress events." sex roles 13:515–524.

carstensen, l. l.; isaacowitz, d. m.; and charles, s. t.(1999). "taking time seriously: a theory of socioemotional selectivity." american psychologist 54:165–181.

dwyer, j. w., and coward, r. t., eds. (1992). gender,families, and elder care. thousand oaks, ca: sage.

dykstra, p. a. (1990). "disentangling direct and indirectgender effects on the supportive network." in social network research, ed. c. p. kees, m. knipscheer, and t. c. antonucci. amsterdam: swets and zeitlinger.

fischer, c. s., and oliker, s. j. (1983). "a research note offriendship, gender, and the life cycle." social forces 62:124–133.

gironda, m.; lubben, j. e.; and atchison, k. a. (1999)."social networks of elders without children." journal of gerontological social work 31:63–84.

johnson, m. p., and leslie, l. (1982). "couple involvement and network structure: a test of the dyadic withdrawal hypothesis." social psychology quarterly 45:34–43.

julien, d., and markman, h. j. (1991). "social support andsocial networks as determinants of individual and marital outcomes." journal of social and personal relationships 8:549–568.

kim, h. k., and mckenry, p. c. (1998). "social networks and support: a comparison of african americans, asian americans, caucasians, and hispanics." journal of comparative family studies 29:313–334.

klein, r., and milardo, r. m. (2000). "the social context of couple conflict: support and criticism from informal third parties." journal of social and personal relationships 17:618–637.

laireiter, a., and baumann, u. (1992). "network structures and support functions: theoretical and empirical analyses." in the meaning and measurement of social support, ed. h. veiel and u. baumann. new york: hemisphere.

lang, f. r. (2000). "endings and continuity of social relationships: maximizing intrinsic benefits within personal networks when feeling near to death." journal of social and personal relationships 17:155–182.

mardsen, p. v. (1987). "core discussion networks of americans." american sociological review 52:122–131.

mccubbin, h. i., and patterson, j. m. (1983). "the familystress process: the double abcx model of adjustment and adaptation." marriage and family review 6:7–37.

milardo, r. m. (1982). "friendship networks in developing relationships: converging and diverging social environments." social psychology quarterly 45:162–172.

milardo, r. m. (1988). "families and social networks: anoverview of theory and methodology." in families and social networks, ed. r. m. milardo. newbury park, ca: sage.

milardo, r. m.; johnson, m. p.; and huston, t. l. (1983)."developing close relationships: changing patterns of interaction between pair members and social networks." journal of personality and social psychology 44:964–976.

pugliesi, k., and shook, s. l. (1998). "gender, ethnicity, and network characteristics: variation in social support resources." sex roles 38:215–238.

roschelle, a. r. (1997). no more kin: exploring race,class, and gender in family networks, thousand oaks, ca: sage.

schonauer, k.; achtergarde, d.; suslow, t.; and michael,n. (1999). "comorbidity of schizophrenia and prelingual deafness: its impact on social network structures." social psychiatry and psychiatric epidemiology 34:526–532.

schweizer, t.; schnegg, m.; and berzborn, s. (1998). "personal networks and social support in a multiethnic community of southern california." social networks 20:1–21.

sluzki, c. e. (2000). "social networks and the elderly:conceptual and clinical issues, and a family consultation." family process 39:271–284.

stein, c. h.; bush, e. g.; ross, r. r.; and ward, m. (1992)."mine, yours, and ours: a configural analysis of the networks of married couples in relation to marital satisfaction and individual well-being." journal of social and personal relationships 9:365–383.

stein, c. h., and rappaport, j. (1986). "social network interviews as sources of etic and emic data: a study ofyoung married women." in stress, social support, and women, ed. s. e. hobfoll. new york: hemisphere.

stoloff, j. a.; glanville, j. l.; and bienenstock, e. j. (1999)."women's participation in the labor force: the role of social networks." social networks 21:91–108.

suitor, j. j., and pillemer, k. (2000). "when experiencecounts most: effects of experiential similarity on men's and women's receipt of support during bereavement." social networks 22:299–312.

titus, s. l. (1980). "a function of friendship: social comparisons as a frame of reference for marriage." human relations 33:409–431.

veiel, h. o. f.; crisland, m.; strosreck-somschor, h.; andherrie, j. (1991). "social support networks of chronically strained couples: similarity and overlap." journal of social and personal relationships 8:279–292.

wellman, b., and wortley, s. (1990). "different strokes from different folks: community ties and social support." american journal of sociology 96:558–588.

wilkinson, d. (1993). "family ethnicity in america" infamily ethnicity: strength in diversity, ed. h. p. mcadoo. newbury park, ca: sage.



Social Networks and Social Support

views updated May 08 2018


It is widely recognized that social relationships and affiliations have powerful effects on physical and mental health. Although many social scientists from Emile Durkheim on have written about the critical role of social relationships in health outcomes, it was not until the 1970s that epidemiologists turned their attention to this issue.

In the first of these studies, in Alameda County, California (Berkman et al., 1979), men and women who lacked ties to others were 1.9 to 3.1 times more likely to die than those who had many contacts. A 1982 study in Tecumseh, Michigan (House et al., 1982), showed a similar association for men, but not for women, between social connectedness and participation and mortality risk. In the same year, D. Blazer reported similar results from a sample of elderly men and women in Durham County, North Carolina.

Schoenbach et al. (1986), in a study in Evans County, Georgia, used a measure of contacts modified from the Alameda County study and found risks to be significant in older white men and women even when controlling for risk factors, although some racial and gender differences were observed. In Sweden, the Goteborg study (Welin et al., 1985) showed that, in different cohorts of men, social isolation proved to be a risk factor for dying, independent of biomedical risk factors. A 1987 report by Orth-Gomér and Johnson reported significantly increased risks for men and women who have been socially isolated. Finally, in a study of men and women in eastern Finland, Kaplan and associates (1988) demonstrated that an index of social connections predicts mortality risk for men but not for women, independent of cardiovascular risk factors.

Several more recent studies, including the Established Populations for the Epidemiologic Study of the Elderly (EPESE) studies, confirm the continued importance of social relationships into late life. Furthermore, studies of large cohorts of men and women in a large health maintenance organization (Vogt et al., 1992) and male health professionals (Kawachi et al., 1996) suggest that social networks are, in general, more strongly related to mortality than to the incidence of disease. Studies in Danish men (Pennix et al., 1997) and Japanese men and women (Sugisawa et al., 1994) also indicate that social isolation and social support are related to mortality. Social networks and support have been found to predict a broad array of health outcomes, from survival after heart attacks to disease progression, functioning, and the onset and course of infectious diseases.


Conceptually, social networks are embedded in a macrosocial environment in which large-scale social forces may influence network structure, which in turn influences a cascading causal process. Serious consideration of the larger macrosocial context in which networks form and are sustained is almost completely absent, and such consideration is needed in studies of social network influences on health.

Networks may operate through at least five primary pathways: (1) provision of social support, (2) social influence, (3) social engagement, (4) person-to-person contact, and (5) access to resources and material goods. These psychosocial and behavioral processes may influence even more proximate pathways to health status, including direct physiological stress responses, psychological states and traits, health-damaging or healthpromoting behaviors such as tobacco consumption or physical activity, and exposure to infectious disease agents.

Most obviously, the structure of network ties influences health via the provision of social support. This framework immediately acknowledges that not all ties are supportive. Social support is typically divided into subtypes, including emotional, instrumental, appraisal, and informational support.

Perhaps even more important than social support are the ways in which social relationships provide a basis for intimacy and attachment. Intimacy and attachment have meaning not only for relationships that traditionally are thought of as intimate (e.g., between partners, between parents and children) but for more extended ties. For instance, when relationships are solid at a community level, individuals feel strong bonds and attachment to places (e.g., a neighborhood) and organizations (e.g., voluntary and religious organizations).

Social networks may also influence health via social influence. Shared norms about health behaviors (e.g., alcohol and cigarette consumption, treatment adherence) might be powerful sources of social influence with direct consequences for the behaviors of network members.

A third, and more difficult to define, pathway by which networks may influence health status is by promoting social participation and social engagement. Getting together with friends, attending social functions, group recreation, and church attendance are all instances of social engagement. Several studies suggest that social engagement is critical in maintaining cognitive ability (Bassuk et al., 1999) and reducing mortality (Glass et al., 2000).

Another pathway by which networks influence disease is by restricting or promoting exposure to infectious disease agents through person-to-person contact. What is perhaps most remarkable is that the same network characteristics that can be healthpromoting can at the same time be health-damaging if they serve as vectors for the spread of infectious disease.

Little research has sought to examine differential access to material goods, resources, and services as a mechanism through which social networks might operate. This is unfortunate, given the existing work showing that social networks operate by regulating an individual's access to life opportunities by virtue of the extent to which networks overlap with other networks. In this way, networks operate to provide access, or to restrict opportunities, in much the same way that social status does.

Lisa F. Berkman

(see also: Community Health; Cultural Identity; Inequalities in Health; Marginal People; Medical Sociology; Psychology, Health; Social Determinants; Sociology in Public Health )


Bassuk, S.; Glass, T.; and Berkman, L. (1999). "Social Disengagement and Incident Cognitive Decline in Community-Dwelling Elderly Persons." Annals of Internal Medicine 131:165173.

Berkman, L., and Syme, S. (1979). "Social Networks, Host Resistance, and Mortality: A Nine-Year Followup of Alameda County Residents." American Journal of Epidemiology 109:186204.

Berkman, L. F. (1995). "The Role of Social Relations in Health Promotion." Psychosomatic Medicine 57: 245254.

Blazer, D. (1982). "Social Support and Mortality in an Elderly Community Population." American Journal of Epidemiology 115:684694.

Cohen, S.; Underwood, S.; and Gottlieb, B. (2000). Social Support Measures and Intervention. New York: Oxford University Press.

Glass, T.; Dym, B.; Greenberg, S.; Rintel, D.; Roesch, C.; and Berkman, L. (2000). "Psychosocial Intervention in Stroke: The Families in Recovery from Stroke Trial (FIRST)." American Journal of Orthopsychiatry 70(2):169181.

House, J.; Robbins, C.; and Metzner, H. (1982). "The Association of Social Relationships and Activities with Mortality: Prospective Evidence from the Tecumseh Community Health Study." American Journal of Epidemiology 116:123140.

Kaplan, G.; Salonen, J.; Cohen, R.; Brand, R.; Syme, S.; and Puska, P. (1988). "Social Connections and Mortality from All Causes and Cardiovascular Disease: Prospective Evidence from Eastern Finland." American Journal of Epidemiology 128:370380.

Kawachi, I.; Colditz, G. A.; Ascherio, A.; Rimm, E. B.; Giovannucci, E.; Stampfer, M. J. et al. (1996). "A Prospective Study of Social Networks in Relation to Total Mortality and Cardiovascular Disease in Men in the U.S.A." Journal of Epidemiological Community Health 50:245251.

Orth-Gomer, K., and Unden, A. (1987). "The Measurement of Social Support in Population Surveys." Social Science Medicine 24:8394.

Pennix, B. W.; van Tilburg, T.; Kriegsman, D. M.; Deeg, D. J.; Boeke, A. J.; and van Eijk, J. T. (1997). "Effects of Social Support and Personal Coping Resources on Mortality in Older Age: The Longitudinal Aging Study, Amsterdam." American Journal of Epidemiology 146:510519.

Schoenbach, V.; Kaplan, B.; Freedman, L.; and Kleinbaum, D. (1986). "Social Ties and Mortality in Evans County, Georgia." American Journal of Epidemiology 123:577591.

Seeman, T. (1996). "Social Ties and Health: the Benefits of Social Integration." Annuals of Epidemiology 6:442451.

Seeman, T., and Berkman, L. (1988). "Structural Characteristics of Social Networks and Their Relationship with Social Support in the Elderly: Who Provides Support." Social Science Medicine 26(7):737749.

Seeman, T.; Berkman, L.; Kohout, F.; LaCroix, A.; Glynn, R.; and Blazer, D. (1993). "Intercommunity Variation in the Association between Social Ties and Mortality in the Elderly: A Comparative Analysis of Three Communities." Annals of Epidemiology 3:325335.

Sugisawa, H.; Liang, J.; and Liu, X. (1994). "Social Networks, Social Support and Mortality among Older People in Japan." Journal of Gerontology 49:S3S13.

Vogt, T. M.; Mullooly, J. P.; Ernst, D.; Pope, C. R.; and Hollis, J. F. (1992). "Social Networks as Predictors of Ischemic Heart Disease, Cancer, Stroke, and Hypertension: Incidence, Survival and Mortality." Journal of Clinical Epidemiology 45:659666.

Weiss, R. S. (1974). "The Provisions of Social Relationships." In Doing unto Others, ed. Z. Rubin. Englewood Cliffs, NJ: Prentice Hall.

Welin, L.; Tibblin, G.; Svardsudd, K.; Tibblin, B.; Ander-Peciva, S.; Larsson, B. et al. (1985). "Prospective Study of Social Influences on Mortality: The Study of Men Born in 1913 and 1923." Lancet 1:915918.

Social Networking

views updated Jun 11 2018

Social Networking

In Internet parlance, a social network is an online community of people interacting over such topics as business, culture, and friendship. Social networks are similar to

forums, but they are more selective in membership and have a clear structure, with each participant usually governing their own online portfolio of personal information and tastes. Online social participants develop relations with other members on the network and create channels of communication between each other, thereby setting up a complex structure. Social networks can be defined by geographic areas, age groups, business interests, informational needs, or other parameters.

Many of the largest social networkssuch as Face-book, MySpace, and LinkedInallow participants to create their own profiles using pictures, videos, links, and other forms of rich media. These types of rich media can also be transferred across the network to friends or associates, making social networks an important, emerging communication tool. While businesses are examining social networks for their marketing and recruitment possibilities, several distinct difficulties have arisen that have affected the profitability of social networks for their owners. Due to these problems, many companies are investing in private social networks designed specifically for business use.


Social networking can be used by companies within their organizations, by establishing the networks over intranet systems. These networks are available only to employees, have safeguards against security threats, and can be used in many different ways. Some businesses may wish to integrate a social network with their company directory so that lists of employee names become profiles through which employees can exchange information and show their interests and expertise. Other businesses may wish to establish intranet forums so that their employees can collaborate in solving specific problems or tackling certain departmental goals. This is especially effective when company departments are centralized and employees cannot see each other face to face.

Businesses are attracted to these company held social networks because of the opportunities for collective problem solving and creative thinking. Employees who are able to discuss options and share information are much more likely to produce innovative solutions to shared problems. Natural teams are often born over such networks, united by needed skills and similar interests. As people become more comfortable communicating in online channels, companies can implement more connecting networks as a form of project management.

Wikis are one of the most popular types of social networks used by businesses. These collaborative networks allow multiple users to edit the same piece of information, contributing other facts or deleting unnecessary content. Online wiki Web sites are considered unreliable due to their free access by all users, but a private wiki can help companies direct teamwork, organize events, update research, and take notes.


In addition to internal networking, companies are also eager to make use of well-established social networks available to other users of the Internet. Certain social networks are directed toward specific industries or certain professionals, designed as problem-solving and research-sharing Web sites. For the more widely available social networks, business interests fall into three main categories:

  • Marketing. Many businesses implement marketing efforts through social networks. Advertisements can be placed in the network Web sites, usually featuring rich media applications involving sound, animation, and interactivity. A company interested in analysis can also embed code in their advertisements that keeps track of how many online users click on their ads, interact with them, and ultimately follow them to company Web sites or online stores.
  • Recruitment. Other companies create their own profiles on such social networks as MySpace so that prospective employees and customers can access a more personalized version of the company Web site where jobs and updates can be posted. Many companies hope to find new employees more quickly through social networking than through job boards, and some social networks such as LinkedIn are based around recruitment possibilities. There have been attempts at creating a resume application by some social networks such as Facebook, but none have been remarkably successful.
  • Communication. Some companies may prefer to communicate to their departments and employees over social networks, updating their social profiles with important information and sending messages to other users. It is more common, however, to do this with private intranet applications.


External social networks, however, have several problems. Those invested in large social networks, such as MySpace and Facebook, are finding it difficult to make a profit with the massive amount of maintenance social Web sites require and the small amount of income so far obtained from advertisement. For others, marketing techniques have proved unsuccessful. Facebook's Beacon application, for instance, was meant to notify users when and what their friends bought on popular online stores, but the

trend-setting idea failed soon after it began when users declined to use it for reasons of privacy. Friends over Web sites, after all, are not always the same as friends face to face. It remains to be seen if external social networks will be able to integrate the proper applications to make themselves a successful tool for businesses or not.


Everywhere and Nowhere. The Economist, 2008. Available from:

Lesnick, Marc. Increasing Internet Community Size and Revenue! Social Networking Conference. Intranet Business Conferences, 2008.

Kirkpatrick, Marshall. Wikis Are Now Serious Business. Read Write Web, 2008. Available from:

McCarthy, Caroline. Forrester: Social Networks Mean Business, Big Business. the social. cnet news, 2008. Available from:

Roberts, Jane. Social Networking for Business Is the Next Big Thing. Commercial Appeal. The E.W. Scripps Group, 8 Jun 2008.

Social Networks

views updated May 18 2018


Social network theory assumes that social interactions have the potential to influence attitudes and behavior. In the sphere of population this assumption has begun to be confirmed by demographers. Network models bear some similarity to diffusion models, but they offer a more structured approach to social interaction by focusing on the specific links that connect individuals and groups. In the 1980s interest in social networks by sociologists led to the collection of network data, the elaboration of theory, and the development of new analytic methods. Demographers have borrowed heavily from this theoretical and methodological work to guide their empirical analyses. Most have concentrated on fertility, investigating the fertility transitions of individuals in local communities, but network approaches have also been used in the study of migration and mortality, clusters of villages, population elites, and organizations.

Evidence that people do indeed talk with friends, relatives, and neighbors about fertility control can be found in historical sources, interviews with elderly people, and surveys conducted in developing countries in the 1960s and 1970s. In these surveys, the content and context of the conversations are missing. When researchers have collected qualitative data, they have found that talk about subjects such as family planning may be open, casual, and quite specific rather than private, formal, and vague. Qualitative data also provide insight into how network partners are selected, an issue relevant for determining appropriate statistical techniques. Both theory and data suggest that social interactions concerning fertility control are especially likely in situations of uncertainty.

Network theory postulates a variety of effects of networks, but in the study of fertility transitions the focus has been on new information transmitted and evaluated in networks and on the influence that networks exert on its members to adopt or resist innovations. Links among network partners are characterized in a variety of ways. An important distinction is that between strong and weak links: strong links are hypothesized to constrain the flow of new information and to exert more social influence than weak links. A variety of indicators of the strength of ties has been proposed, such as whether the network partner is a confidant, a friend, or an acquaintance and the duration of the relationship. Networks have also been characterized by the degree of homogeneity of members with respect to characteristics such as age, education, gender, and ethnicity. Heterogeneous networks may facilitate the spread of new information, whereas homogeneous networks may be more effective in exerting social influence.

Studies using cross-sectional data provide convincing evidence of an association between the attitudes and behavior of individuals and the characteristics of their networks. For example, the probability that a woman is using contraception is typically higher if her network partners are also using contraception, and the method she uses is likely to be the same as the methods used by those with whom she interacts. This probability has been found to depend also on the characteristics of the individual and her networks, as well as on the particular context; networks may also impede contraceptive use. Because of the dearth of network data, some analysts have used aggregate data to represent local or transnational networks, again finding associations that suggest the importance of networks.

While there is a clear empirical association between network characteristics and attitudes and behaviors, establishing a causal effect of networks on attitudes and behaviors has been difficult. Because actors may select those with whom they discuss topics such as family size and family planning or whether and when to migrate, determining the direction of causality requires longitudinal data or analytic techniques that take the selectivity of networks into account.

In summary, empirical work by demographers has established the potential significance of network approaches for examining processes of demographic change. By implication, analyses that treat individual actors in isolation are not sufficient. Fully realizing this potential may require further theoretical development; it will certainly require new efforts at data collection, including qualitative and survey data on the links among network partners, as well as further development of analytic techniques.

See also: Diffusion in Population Theory; Fertility Transition, Socioeconomic Determinants of; Social Capital.


Bongaarts, John, and Susan C. Watkins. 1996. "Social Interactions and Contemporary Fertility Transitions." Population and Development Review 22: 639–682.

Casterline, John B. 2001. "Diffusion Processes and Fertility Transition: Introduction." In Diffusion Processes and Fertility Transition, ed. John B. Casterline. Washington, D.C.: National Academy Press.

Entwisle, Barbara., Ronald R. Rindfuss, David K. Guilkey, Apichat Chamratrithirong, Sara R. Curran, and Yothin Sawangdee. 1997. "Community and Contraceptive Choice in Thailand: A Case Study of Nan Rong." Demography 33:1–11.

Kohler, Hans-Peter. 2001. Fertility and Social Interaction. Oxford: Oxford University Press.

Kohler, Hans-Peter, Jere R. Behrman, and Susan C. Watkins. 2001. "The Density of Social Networks and Fertility Decisions: Evidence from South Nyanza District, Kenya." Demography 38: 43–58.

Montgomery, Mark R. and John B. Casterline. 1996. "Social Influence, Social Learning, and New Models of Fertility." In Fertility in the United States: New Patterns, New Theories, ed. John B. Casterline, R. D. Lee, and K. A. Foote. Supplement to Population and Development Review. New York: Population Council.

Valente, Thomas W. 1995. Network Models in the Diffusion of Innovations. Cresskill, NJ: Hampton Press.

Susan Cotts Watkins

social network

views updated Jun 11 2018

social network See NETWORK.

About this article

Social Networks

All Sources -
Updated Aug 18 2018 About content Print Topic