A quick definition of contact chaining: a graph of the (human) network neighborhood around any specific individual -- it shows everyone who is one and two steps/hops away from the individual of interest. A contact chaining map also shows how everyone in the network neighborhood is connected to each other. Contact chaining can easily be performed using the call and email meta-data the NSA is collecting.
Below is a 2-step contact chaining network of the 9/11 hijackers (after the attack) it shows how quickly a network expands from just one or two suspects. The network was created using a contact chaining algorithm from two initial Al Qaeda suspects known to be living in the USA and spotted attending Al Qaeda meetings abroad. For more information, see this detailed analysis of how social network analysis can be used to track known suspects.
Business consultants also use "contact chaining"— we just call it something else: network neighborhood. We use it in a similar way — to see who is near and interconnected around a specific individual.
Below is the organizational network of one of our business clients. Two nodes(people) are connected by a grey line if they have a strong work link between them (they exchange key information, documents and data on a frequent basis). The nodes are colored by the type of work they do.
As with many organizations, they have many employees (baby-boomers: born 1946-1960) who are retiring, or about to. While performing an organizational network analysis for this client, we also investigated what affect the upcoming retirements would have on their organization. An employee (#128) who is about to retire is highlighted and shown in the above map with the large black arrow. He appears to be well connected — many strong work ties throughout the organization.
Below is the same organizational map, but this time after contact-chaining, showing the how many other employees will be affected by this employee's retirement. The affected employees are all highlighted in yellow.
We see that the affect of this retirement will reach into many parts of the company. To see exactly who will be influenced by this retirement, we hide the non-affected nodes, to reveal the two-step network neighborhood around the retiring employee. Since this is actual data from a real company, we have hidden the employees names and using non-associated numbers.
Who is about to retiree in, or leave, your organization? What ripple effect will they have when they are gone? What (work) chains will they break? Whose job will be affected by the vacancy? Do you have an effective replacement? These are all key questions that Management and Human Resources must have answers to, and a plan for, as many people prepare to leave their current employers.