Network Analysis Research Paper

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Network analysis is a cluster of methodological techniques for the mathematical description and investigation of networks. It has applications across both the natural and the social sciences. Electronic networks, river networks, etymological networks, epidemiological networks, and networks of economic transactions have all been subjects for network analysis. In  the social sciences, the concern is with the investigation of social networks. A social network is any articulated pattern of connections in the social relations of individuals, groups, and other collectivities. Social networks include friendship and kinship networks, interorganizational networks, communication  networks, scientific citation networks, and policymaker networks. Social network analysis, then, deals with relational data in all areas of social life. It handles the contacts, ties, and connections, group attachments, and meetings that relate one  person  or  group  to  another  and  that  cannot  be reduced to the properties of the individual agents themselves. Such relational data are central to the building of models of the structures through which action is organized. Social network analysis is not limited to small-scale and interpersonal structures, and there have been many applications to such phenomena as global trading relations in world systems.

Social network analysis developed independently in the social anthropology of small societies and the social psychology of  small  groups.  Anthropologists such  as Alfred Radcliffe-Brown (1881–1955) pioneered a view of social structure as a “web” of social relations and an idea of actions “interweaving” and “interlocking” through such a network of connections. Anthropologists in this tradition began to investigate the “density” of these social networks and the “centrality” of individuals within them. Small group researchers in the Gestalt tradition developed ways of investigating the pattern of relations within the “life space” of social groups, the most influential example of this being Jacob Moreno’s (1892–1974)  sociometric studies of schoolroom friendship choices. The study of “group dynamics” developed rapidly from the 1950s with more formal applications of the network idea.

Contemporary network analysis grew markedly from the early 1970s, when a group of students and researchers working with Harrison White began to explore the use of more formal mathematical models for the analysis of small group and anthropological data and began to extend these investigations to wider sociological phenomena. A landmark study from this burgeoning work was Mark Granovetter’s  Getting a Job (1974). Granovetter showed that  people’s chances of getting information  about job opportunities depended not on the formal methods of job search that they used but on their location in informal social networks. Counterintuitively, he also showed that having a small number of “weak” ties was far more important than having many “strong” ties: information came from “acquaintances” rather than close “friends” and relatives. This  group  of researchers used algebraic models from set theory and ideas from the mathematical theory of graphs, along with methods of multidimensional scaling. Together, this cluster of methods established a framework of network analysis that spread rapidly across sociology and into the other social sciences.

The basic idea in social network analysis is that  a social network can be modeled as a set of “points” connected by “lines,” the points representing the individuals and groups, and the lines representing their social relations. The simplest applications involve drawing a graph of points and lines to represent a social network and then visually examining the pattern of lines for its structural properties. When dealing with more than a small number of points, however, more abstract methods are necessary, and the mathematical methods allow the points and lines to be recorded in a matrix ready for mathematical processing. This has allowed the investigation of such structural properties as the  density of relations, the  centrality of agents, the formation of cliques and components, and the assessment of social distance. A measure of density, for example, assesses the proportion of all possible relations that actually exist in a network and is an important indicator of solidarity and cohesion. Cliques are subnetworks into which networks may be divided and that may comprise groups capable of independent  action. Centrality concerns the strategic positions that actors may hold in the  overall pattern  of connections and  the  consequent flow of influence, support, or power.

Important applications of network analysis have been undertaken in many areas of the social sciences. Claude Fischer (1982) and Barry Wellman (1979) investigated community  networks in cities with high levels of geographical mobility,  and  they  explored  the  increasing reliance that people have placed on electronic methods and virtual channels of communication for maintaining interpersonal cohesion. The work of Robert Putnam was influential in advocating the idea that people’s networks of social relations could be regarded as forms of social capital.  This  view has been  elaborated in  the  competing approaches of Nan Lin (2001) and Ron Burt (2005). Lin stresses individual investments in social relations and the rational actions that are involved in the accumulation of social capital. Burt has looked at processes of brokerage and social closure—rooted in measures of centrality and prominence—for the creation of social capital.

Jim Bearden and  various coworkers have explored structures of interlocking directorships in business, examining the nature and significance of bank centrality within financial networks (Mintz  and  Schwartz 1985).  David Knoke has pioneered methods for studying networks of political connection and influence, leading to numerous studies of policy networks and the role of power in the policy process (Knoke et al. 1996). Peter Bearman (1993) is one of a number of researchers who has demonstrated the uses of network analysis for historical data on stratification and power relations. Many important studies have been undertaken on organizational networks in business, and these have been extended into work on knowledge management by Rob Cross (Cross and Parker 2004) and David Snowden (Kurtz and Snowden 2005). Important methodological work includes that of Linton Freeman on approaches to  network visualization, using methods of pictorial display for the analysis of large social networks. These have been used in his own study of the development of social network analysis (Freeman 2004).

Applications of social network analysis have tended to be  both  descriptive and  static,  leading  many  to  ask whether network analysts are doing anything more than producing pretty pictures and arbitrary numbers. This has been reinforced by the incursions of many physicists into the  area  of  network  analysis. These  physicists have argued—often in  ignorance of what work has actually been undertaken by social network analysts—that their methods have far more to offer in the analysis of social relations (Watts 2003). What  is clear, however, is that these discussions have begun to shift social network analysis toward a greater concern for explanation, rather than simply  description,  and  toward  the  investigation of dynamic processes in social networks.

The need to combine network analysis with agentlevel models has been emphasized by Mustafa Emirbayer and  his  colleagues (Emirbayer  1997;  Emirbayer  and Goodwin 1994), who stress the interdependence of cultural, structural, and agency analyses. Network analysis must be combined with an awareness of the culturally formed  subjective motivations  and  commitments  of actors, whose intentional actions produce, reproduce, and transform network structures. This model of the structuration of social networks stresses the iterative nature of rule-governed actions. This is echoed in the growth of agent-based computational methods of network analysis that propose ways of linking microlevel decision making with macrolevel structural change (Monge and Contractor 2003).

Bibliography:

  1. Bearman, Peter. Relations into Rhetorics: Local Elite Social Structure in Norfolk, England, 1540–1640. New Brunswick, NJ: Rutgers University Press.
  2. Burt, Ronald 2005. Brokerage and Closure: An Introduction to Social Capital. New York: Oxford University Press.
  3. Carrington, Peter , John Scott, and Stanley Wasserman, eds. 2005. Models and Methods in Social Network Analysis. New York: Cambridge University Press.
  4. Cross, Rob, and Andrew Parker. The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations. Cambridge, MA: Harvard Business School Press.
  5. Emirbayer, M 1997. Manifesto for a Relational Sociology. American Journal of Sociology 103 (2): 281–317.
  6. Emirbayer, Mustafa, and Jeff G 1994. Network Analysis, Culture, and the Problem of Agency. American Journal of Sociology 99 (6): 1411–1454.
  7. Fischer, Claude 1982. To Dwell Among Friends: Personal Networks in Town and City. Chicago: Chicago University Press.
  8. Freeman, Linton 2004. The Development of Social Network Analysis: A Study in the Sociology of Science. Vancouver, BC: Empirical Press.
  9. Granovetter, Mar 1974. Getting a Job: A Study of Contacts and Careers. Cambridge, MA: Harvard University Press. 2nd ed.
  10. Chicago: University of Chicago Press.
  11. Knoke, David, Franz Pappi, Jeffrey Broadbent, and Youtaka Tsujinaka. 1996. Comparing Policy Networks: Labor Politics in the U.S., Germany, and Japan. New York: Cambridge University Press.
  12. Kurtz, Cynthia F., and David Snowden. 2005. The New Dynamics of Strategy: Sense-making in a Complex and Complicated World. IBM Systems Journal 42 (3): 462–483.
  13. Lin, N 2001. Social Capital: A Theory of Social Structure and Action. Cambridge, U.K.: Cambridge University Press.
  14. Mintz, Beth, and Michael Schwar 1985. The Power Structure of American Business. Chicago: University  of Chicago Press.
  15. Monge, Peter , and Noshir Contractor. 2003. Theories of Communication Networks. New York: Oxford University Press.
  16. Scott, J 2000. Social Network Analysis: A Handbook. 2nd ed. London: Sage.
  17. Scott, J 2002. Social Networks: Critical Concepts in Sociology. 4 vols. London: Routledge.
  18. Wasserman, Stanley, and Katherine F 1994. Social Network Analysis: Methods and Applications. New York: Cambridge University Press.
  19. Watts, Duncan 2003. Six Degrees: The Science of a Connected Age. New York: Norton.
  20. Wellman, Barry. The Community Question: The Intimate Networks of East Yorkers. American Journal of Sociology 84: 1201–1231.
  21. Wellman, Barry, and Stephen Berkowitz, eds. 1988. Social Structures: A Network Approach. Cambridge, U.K.: Cambridge University Press.

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