Web 2.0 and Emerging Learning Technologies/Social Network Analysis

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Social Network Analysis (SNA), is a type of research method. Since the concept of a social network was first used to analyze the structure of fishing in Norway by Barnes (anthropologist) in 1954, many researchers have been using this method to do research in social structures. With the coming of the era of Internet focusing on interactive communication, this method begins to be used to analyze the more complex Interpersonal communications in Network Virtual Community.

Fields in which SNA plays role[edit]

  1. Psychology
  2. Anthropology
  3. Mathematics
  4. Communication
  5. Sociology
  6. Statistics[1]

How to do SNA[edit]

About three steps:

  1. Record and Analyze original data;
  2. Express data in form of visualization with some tool's help;
  3. Analyze the above data more, distill the important problems and make conclusion.

Tools for SNA[edit]

  1. Description of Ucinet
  2. Description of NetDraw[2]
  3. Pajek,Pajek is a program (for Windows) for large network analysis and visualization. It is freely available for noncommercial use.Besides ordinary networks,Pajek also supports multi-relational and temporal networks.
  4. Onasurveys.com: Online Social Network Analysis survey tool for data collection. Exports data to NetDraw, Inflow and Excel.

Famous SNA Researchers and relative research websites[edit]

Researchers
  1. Linton C. Freeman: Research Professor, Department of Sociology and Institute for Mathematical Behavioral Sciences School of Social Sciences, University of California.
  2. Steve Borgatti: Professor at the University of Kentucky in the Gatton College of Business and Economics.
  3. John Scott: Professor in the Sosiologisk Institutt at the University of Bergen, Editor of the European Societies, the journal of the European Sociological Association.
  4. Patrick Doreian: Professor, Department of Sociology, University of Pittsburgh.
  5. Wayne Baker: Professor of Management & Organization Professor of Sociology Faculty Associate, Nonprofit and Public Management Center Faculty Associate, institute for Social Research.
  6. Jonathon N. Cummings: Associate Professor of Management Fuqua School of Business Duke University.
  7. Ronald L. Breiger: Professor, Department of Sociology, University of Arizona.
  8. David Krackhardt: Professor of Organizations at the Heinz School of Public Policy and Management and the Tepper School of Business, Carnegie Mellon University
Research websites
  1. International Network for Social Network Analysis
  2. International Center for Research on SNA in Business

Case Study[edit]

To prove the key role SNA plays,Professor Steve Borgatti from University of Kentucky has ever conducted a social network analysis of executives in the exploration and production division of a large petroleum organization with his colleagues' help.[3]

This research is interested in assessing the executives'ability as a group to create and share knowledge.The researchers mainly conducted a social network analysis of information flow among the top 20 executives within the Exploration and Production Division.This analysis reveals a striking contrast between the group’s formal and informal structure.

From this contrast,we can find three important points quickly emerge for this group in relation to sharing information and effectively leveraging their collective expertise.

The social network analysis identified mid-level managers who were critical in terms of information flow within the group. A particular surprise came from the very central role that Cole (a member) played in terms of both overall information flow within the group and being the only point of contact between members of the production division and the rest of the network. In this network, Cole is a critical source for all sorts of information.Through no fault of his own, the number of informational requests he received and the number of projects he was involved in had grown excessive,which not only caused him stress but also frequently slowed the group as a whole, because Cole had become a bottleneck. The social network analysis also revealed the extent to which the entire network was disproportionately reliant on Cole.If he were hired away, the efficiency of this group as a whole would be significantly impacted as people in the informal network reestablished important informational relationships. The social network diagram made it very clear that if Cole left, the company would lose both his valuable knowledge and the relationships he had established that in many ways were holding the network together. However, with the analysis' help, we can make a central intervention to reallocate many of the informational requests coming to Cole to other members in the group. Simply categorizing various informational requests that Cole received and then allocating ownership of these informational or decision domains to other executives served to both unburden Cole and make the overall network more responsive and robust.

Just as important, the social network analysis helped to identify highly peripheral people who essentially represented untapped expertise and thus underutilized resources for the group.In particular, it became apparent that many of the senior people had become too removed from the day-to-day operations of this group. The most senior person (Jones) was one of the most peripheral in the informal network. This is a common finding. As people move higher within an organization, their work begins to entail more administrative tasks that makes them both less accessible and less knowledgeable about the day to day work of their subordinates. However, in this case Jones had become too removed,and his lack of responsiveness frequently hold the entire network back when important decisions needed to be made. In this case, the social network diagram helped to make what could have been a potentially difficult conversation with this executive nonconfrontational, and results in more of his time being committed back to the group.

Finally,the social network analysis demonstrates the extent to which the production division has become separated from the overall network.Several months before this analysis,these people had been physically moved to a different floor in the building. Upon reviewing the network diagram,many of the executives realized that this physical separation had resulted in loss of a lot of the serendipitous meetings that occurred when they were co-located.

In this case,the executives decided that they needed to introduce more structured meetings to compensate for this recent loss of serendipitous communication(and they also adopted an instant messaging system to promote communication).

References[edit]

  1. http://www.analytictech.com/networks/history.htm
  2. http://www.analytictech.com
  3. Cross, R., Parker, A., Prusak, L. & Borgatti, S.P. 2001. Knowing What We Know: Supporting Knowledge Creation and Sharing in Social Networks. Organizational Dynamics 30(2): 100-120.