Social Network Analysis

1.     The definition and significance

Social network analysis (SNA) is an approach and set of techniques adopted to study and analyze the exchange of resources among individuals, teams, groups, departments, or even entire organizations and etc., which can be collectively named as actors (Haythornwaite, 1996). SNA provides a rich and systematic method to evaluate informal networks by mapping, measuring and analyzing relationships among actors (Cross, Parker, Prusak, & Borgatti, 2001).

SNA provides particular understandings about how actors connect and interact with each other in organization or in society, determines ways to consider diverse social structures, reveals issues and difficulties to measure phenomena. This relation analysis amongst numerous actors provides insight into communication links, locates the crucial actors in the information transmission and reveals structural holes in the social networks where the communication flows between nodes are inhibited. For instance, Rogers (2003) and Cross and Parker (2004) demonstrated the processes of building bridges amongst various subgroups in the organization, using SNA, to investigate how organizations became more efficient and sustainable (Valente 2010).
 

Figure1. Social Network Analysis
 

2.     Measurement

To assess the significance and contributions of each particular actor, SNA provides several measuring methods, in which, degree, closeness and centrality, as the most important and popular concepts, are detailed in the last lecture.

3.     An application of SNA – Pathological gambling

SNA is a powerful tool with increasing applications in social sciences and has been adopted in various areas (e.g., psychology, health, business organization and electronic communications) by examining the informal connections between factors.

Meisel, MK., Clifton, AD., MacKillop, J. etc. illustrated a research of how social network interacts with individuals on pathological gambling using SNA, in 2014. Will social factors initiate and maintain the behavior of gambling? The answer is yes, according to the paper. As shown in the two graphs (Figure2. (a)&(b)), darker colors and larger nodes stand for more frequent gambling, smoking and drinking behavior. Obviously, in PG network, a greater occurrence of gamblers is exhibited. On the contrary, the NPG participant comprised a network with few addictive behaviors, which are restricted to more distinct subgroups of associates
 

              

(a) Non-pathological gamblers (NPG) network’s gambling

 

(b) Pathological gamblers (PG) network’s gambling 

Figure2. Structural social networks of gambling

I personally believe that the social networks that we involved in deeply, would affects our thoughts, perspective, view, behavior, even our life.

 

References

[1] Haythornwaite, C., 1996, Social network analysis: An approach and technique for the study of information exchange, LISR, 18, 323–342.

[2] 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, 100–120.

[3] Valente TE, 2010, Social Networks and Health, Models, Methods and Applications, Oxford University Press, Oxford.

[4] Meisel, MK., Clifton, AD., MacKillop, J. etc., 2014, Egocentric social network analysis of pathological gambling.

[5] Social network analysis [Online] http://wenku.baidu.com/link?url=5iakzIF2dQ1FiZiKSjUYxxZe-KyNg0dh8b5KtahIlZflqyAM5Ma-_op1R_kPhqbotbJ7A4cOTCDgSIRQSYwRSNhDI-yktOduw8KILKHRB3G Access at 16/Oct./2014.

[6] NodeXL [Online] http://research.microsoft.com/en-us/projects/nodexl/ Access at 16/Oct./2014.