The concepts of “betweenness centrality” and “structural holes” are some of the most powerful in the social network analysis toolset (pun intended - but forgive me for lumping the two concepts together for this post). In a nutshell, high betweenness indicates that the overall network is disproportionally reliant on an individual for communication between points in the network, resulting in a “broker” advantage. There are plenty of books and articles that demonstrate the advantages gained by a high betweeness, but it seems to me that few if any actually demonstrate the process by which network position is leveraged for maximum gain. Like all network measures, betweenness is a measure of potential, and the high-betweenness individual must

• be aware of the advantage of their position (that they bridge two+ disconnected alters with a common need or interest, and know what that need or interest is)
• be motivated to take advantage of their position
• must avoid losing their position (avoid letting their connections bypass them)
• must have sufficient information to broker (the ability to extract and selectively communicate information)

Some time ago, I decided to utilize what I know about networks to help me negotiate resort peak season hotel packages for a large seminar I was organizing, including discount room rates, amenities, and conference hall rentals. It was my first experience negotiating this sort of thing, and it made me aware that information gathering (research) is a critical component for translating network position into network advantage.

Here is the process I used, that worked phenomenally well:

1. I requested generic package rates and deals from a dozen roughly comparable hotels.
2. I picked 5 hotels (based upon personal preference), and mix-and-matched the best offers from each hotel into one “ideal” package even though the hotels were not strictly comparable (some were on the beach, some weren’t). For example, one hotel would offer lower room rates and free parking / spa access, another would offer a less expensive conference hall, another would offer VIP upgrades for speakers, etc.
3. I individually contacted each hotel, letting them know I was receiving quotes from their competitors (and whom those competitors were), as well as the current “package” I was looking at. It helped to let them know I was strongly considering them, but I was working with a committee that might have to make a decision based upon “best cost”.
4. I asked the current hotel if they could improve their offering in any way to help sway the decision process. If the hotel improved their prices or offerings, I would then go to the next hotel with the “improved ideal package”, repeating this step until the hotels stopped improving their offers or response delay started becoming substantial.
5. I then picked the best offer on the table mixed with personal preference.

I had to repeat step 4 with all five hotels about 2 or 3 times, and each time every hotel would improve one feature of their package (price, amenities, upgrades) a little bit, thus forcing their competitors to reciprocate. It was in effect the process of intentionally creating the “prisoner’s dilemma” among them; if at any point they were willing to actually contact the competing hotels and work among themselves, they would have negated all of my negotiating advantage.

The critical lesson about extracting power and advantage from network position relies on the ability to gather and selectively share information about one’s alters.

For the network analyst, this means that betweenness measurements only really become useful when the analyst digs deeper into the context of the network to understand precisely what can be leveraged for local advantage.  Perhaps there is an opportunity for natural language processing/mining to augment social network analysis in this regard.

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