Social Network Analysis Essay

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Social network analysis developed from diverse sources, including anthropological accounts of detribalized urban migrants, surveys of people’s long-distance communities, political upheavals, Internet connectivity, and trade relations among nations. The Internet, inherently network-like, has so popularized the approach that Business Week named social network analysis the hottest new technology” of 2003, and membership in network analysis’ professional organization has doubled in four years.

Social network analysts reason from whole to part; from structure to relation to individual; from behavior to attitude. They argue that their social structural explanations have more analytic power than individualistic analyses that do not take relational patterns into account and that interpret behavior in terms of the internalized norms of discrete individuals. The structure of a network, the relations among network members, and the location of a member within a network are critical factors in understanding social behavior. Analysts search for regular structures of ties underlying often incoherent surface appearances, and they study how these social structures constrain network members’ behavior. Key concepts include network density, centrality, transitivity, tie strength, clustering, and structural equivalence.

Social networks are formally defined as a set of nodes (or network members) that are tied by one or more specific types of relations. In much research, these nodes are individual persons, but they can also be groups, corporations, households, blogs, nation-states, or other collectivities. Ties consist of one or more specific relations, such as financial exchange, friendship, hate, trade, web links, or airline routes. Ties vary in quality (whether the relation provides emotional aid or companionship), quantity (how much emotional aid; how frequent the companionship), multiplexity (sometimes called multistrandedness: ties containing only one relation or several), and symmetry (resources flowing in one direction or both). The non-random structure of ties channels resources to specific locations in social systems, fostering inequalities.

Several analytic tendencies distinguish network analysis. First, there is no assumption that groups are the building blocks of society. While social network analytic techniques can discover the empirical existence of groups, the approach is open to studying less-bounded social systems. For example, researchers have mapped the structure of the World Wide Web on the Internet, showing how superconnectors shorten distances between websites.

Second, although social network data often include information about the attributes of individuals, such as age, gender, and beliefs, individuals are not treated as discrete units of analysis. Instead, analysis focuses on how the networks affect the individuals and ties embedded in them.

Third, social network analysis contrasts with analyses which assume that socialization into norms determines behavior and social structure. By contrast, network analysis looks to see the extent to which patterns of social relations affect norms and values.

Social network analysts gather data in many ways, such as ethnography, surveys, archives, and simulations. Their data collection emphasizes ties and the problematic nature of boundaries. Although analysts often visualize networks as point and line graphs, they analyze them as matrices that are more amenable to statistical and mathematical manipulation.

Bibliography:

  1. Carrington, P., Scott, J., & Wasserman, S. (eds.) (2005) Models and Methods in Social Network Analysis. Cambridge University Press, Cambridge.
  2. Freeman, L. (2004) The Development of Social Network Analysis. Empirical Press, Vancouver.
  3. Scott, J. (ed.) (2002) Social Networks: Critical Concepts in Sociology, 4 vols. Routledge, London.
  4. Wellman, B. (ed.) (1999) Networks in the Global Village. Westview Press, Boulder, CO.

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