Social Network Analysis

Social Network Analysis is

Social Network Analysis is also a key component of Power Structure Research

Background

Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers, web sites, and other information/knowledge processing entities. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA].

To understand networks and their participants, we evaluate the location of actors in the network. Measuring the network location is finding the centrality of a node. These measures give us insight into the various roles and groupings in a network -- who are the connectors, mavens, leaders, bridges, isolates, where are the clusters and who is in them, who is in the core of the network, and who is on the periphery?"

Uses

Marketing and data mining

Sales, marketing and customer retention campaigns are set to become smarter, more effective and more profitable thanks to a new social network analysis module from data mining automation vendor KXEN. By exploiting the connections between customers of telcos, banks, retailers and others, KXEN’s new KSN module has shown more than 15% lift improvement in campaign results.

KSN identifies the otherwise hidden links – call records or bank transfers for instance – between friends, families, co-workers and other communities and extracts significant social metrics, pinpointing who are the best connected and who plays the most important role in any group. In this way it reveals valuable new customer intelligence that – when added to existing customer information – can strengthen significantly user organisations’ customer acquisition, retention, cross-sell and up-sell campaigns.

Using KSN, companies can increase the accuracy and precision of their campaigns by leveraging the many more customer attributes that the module reveals, allowing them to better predict when customers may be about to churn to another provider, close an account, or buy a new product. A feature unique to KXEN allows the analysis of multiple networks and their evolution over time, exposing specific patterns of behaviors like rotational churn, fraud and identity theft.

Fetishising Social Network Analysis

Bill Domhoff argued in 2005 that many present day adherents of social network analysis have forgotten its important links to questions of power:

those who practice in the burgeoning field of network analysis ignore the early corporate interlock studies and continue to use hypothetical or small-group data for the most part while they hone their methodologies. It is as if these rigorous people are embarrassed by part of their early history.

Resources

• Jiscmail list SNA 'The list will facilitate discussion of social network analysis amongst interested UK academics, and will facilitate organisation of off-line meetings.'

Visualisation

• http://sourceforge.net/projects/socnetv

Data sources

• Letters written on behalf and in support of Scooter Libby to the judge that sat on his case: http://online.wsj.com/public/resources/documents/libbyletters20070605.pdf

Further Reading

• Robert A. Hanneman and Mark Riddle (2005) Introduction to social network methods Riverside, CA: University of California, Riverside ( published in digital form at http://faculty.ucr.edu/~hanneman/ )

• Bibliography This page is part of an on-line text by Robert A. Hanneman (Department of Sociology, University of California, Riverside) and Mark Riddle (Department of Sociology, University of Northern Colorado).

See Also

• Power Structure Research | Investigative Research |