Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.



Published on

Published in: Technology, Education
  • Be the first to like this


  1. 1. Social Network Analysis‘...a central Jack or a periphery Bob?’ -Alcott & Christopoulos
  2. 2. Network TypeExample: Ego-Centric• Ties in these networks are defined by a single central actor/node (including perceived ties between other actors).• Ego-centric networks ...provide network analysts and researchers with interesting and useful data about the roles individuals adopt… -FisherAlternatives:• Socio-centric• One Mode• Two Mode
  3. 3. Network DensityExample: Sparse• Ego-centric networks are vulnerable if the central node is removed and you are unable to recruit any other actor who is structurally equivalent.Alternatives:• Dense – networks where the majority of nodes are directly linked to each other are more resilient as there is little/no disruption to communication flows if an actor is removed.
  4. 4. CliquesExample: 16, 7, 8• A clique is a subgroup of actors who are all directly connected to one another and no additional network member exists who is also connected to all members of the subgroup. -Hawe, Webster & Shiell
  5. 5. BrokersGood or bad?• Described as …individuals who are the glue that holds a social network together …• In most cases, knowledge brokers are good, but there are times when they are hoarders of information or power brokers. -Tennant
  6. 6. PeripheralsNot necessarily out-on-a-limb...Remember: ...some organisations within an inter-organisational network can exercise power by refusing to lend their credibility to the network. They remain on the periphery structurally, but are able to influence the direction the network takes entirely because of their size, reputation, or through the power of sanctions. -Hawe, Webster & Shiell
  7. 7. Advantages of SNA • Key actors identified by the network are often missed by hierarchical/organisational related approaches. • Visual impact: From a good visualization, the observer can begin to understand communication patterns, including who on the nursing unit may influence the flow of information (e.g., act as a gatekeeper) or who has more or authority due to their coordination role in the network. -Effken & Benham-Hutchins
  8. 8. Limitations of SNA • Identifying isolates in the workplace/school setting etc must be approached with caution • Findings tend to represent ‘snapshots’; follow-up investigation often recommended to spot trends over time • Often survey-based; vulnerable to low response rate and inaccuraciesImage credit: spaceodissey via flickr
  9. 9. SNA in action: business connectivity in Bristol• ‘Engaging with this project, individual actors have been able to discern weaknesses in their network position and detect opportunities in those that reciprocate a collaboration interest.• At the same time they have been able to gain an overview of the structure of interactions among others and potentially determine an optimal strategy for their own network interactions.• By improving on their cognitive map of the network they are effectively improving their horizon and making an informed decision on whether it is best for them to meet a central Jack or a peripheral Bob. ‘ -Alcott & Christopoulos
  10. 10. Bibliography• ALCOTT, T. and CHRISTOPOULOS, D.C . (2011). Is it important to know Jack? Using social network analysis to assess regional business connectivity in Bristol. [online]. Procedia - Social and Behavioral Sciences, 10, 90-97. Last accessed 15 July 2012 at:• EFFKEN , J. and BENHAM-HUTCHINS, M. (2011). Technology-Enhanced Social Network Analysis: An Old Idea Whose Time Has Come—Again. (Issues, Impacts and Insights Column). [online]. Online Journal of Nursing Informatics (OJNI),15 (1). Last accessed 15 July 2012 at:• FISHER, D. (2005). Egocentric Networks To Understand Communication. [online]. IEEE Internet Computing. 9(5). Last accessed 15 July 2012 at:• HAWE, P., WEBSTER, C. and SHIELL, A. (2004). A glossary of terms for navigating the field of social network analysis. [online] Journal of Epidemiol Community Health. 58:971-975. Last accessed 15 July 2012 at:• TENNANT, N. (2012). Social Networks for Talent Identification: Is the 9-Box Dead? [online]. Management Innovation eXchange. 24/04/12. Last accessed 15 July 2012 at: identification-9-box-dead