Communication Method, Scale, and Entropy

In a surprise to Marshall McLuhan, we see ad hoc conversations conducted through different electronic media demonstrating very similar scaling characteristics across number of nodes, number of edges, and number of unique edges.  Looking at email lists, IRC, and long-term twitter searches, we more similarity than difference between the three media.

However, when look at the observed conditional entropy (below the fold), the differences become clear: communication patterns are very different by media type, even as the networks scale similarly in communicants.  Maybe McLuhan was right.

nodes vs unique edges

nodes vs total edges

unique vs total edges

 

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Bailouts: Understanding Risk in a Networked Economy

Individual power increases network risk. When the power goes, so does the network.

But, this risk can also mobilize everyone else to buoy up the network by supporting the powerful (AIG rescue) or group cooperation (bailout lobbying).  When a power fails, there will be painful redistribution of wealth (Lehman Brothers) and the market as new relationships are established.  The market redistribution remains to be seen, but JPMorgan’s buying up relationships (the network) left and right.

Recommendations to the survivors. It’s easier to buy existing relationships through M&A than to create them from scratch, so think specific geographies and buy local; that’s where you’ll find the majority of relationships. For all those new customers you acquire reach out to them early and often.  Build the relationships that kept them with your acquiring company.

Network risk is inherent to trading, and traders will never willingly open their books. The bulk of a trader’s value is in his judgment, not the actual trading.  If you knew what they were buying and selling, you could duplicate their portfolio without paying their fees.  But, there’s an opportunity for a new Moody’s: grade trading funds on network risk.

Visualizing Your Professional Networks

Erich's LinkedIn
17,000+ on LinkedIn

I spend much of my waking time thinking about how relationships between individuals in groups effect the behavior of the individuals and of the group itself. One tool I recently put together looks at professional relationships from LinkedIn.com.

Attached is a representation of the relationships between the 17,000 people my work contacts know. This is how we know us.

If you want to know what your network looks like, drop me a line.