Martin Krzywinski at the Genome Sciences Centre of the BC Cancer Agency, created software called Circos designed to help elucidate the interaction of genes, and has used it to create some truly beautiful graphs.
The software is pretty complex, and I have only figured out how to use his simple on-line version, which limits the number of inputs. But, even so, here is an image I created using Circos. The image represents the number of emails exchanged by the top 10 most connected participants with each other, from an active large email list.
I always enjoy analyzing social networks (SN’s) that have had a lot less press than the Goliaths of MySpace and Facebook. I have done an awful lot of them, but one of my favorites was looking at the co-sponsorship patterns in the US Senate, 110th session (the current one).
This analysis was especially enjoyable because the graph is just one giant cluster, so conclusions took some real digging. So, what did we learn?
We learned a few things: graphs are just the beginning of analysis (but we knew that already); not all junior Senators are as strategic as others; and directionality of the relationships can have a large impact.
There are a handful of junior Senators setting themselves up for favor by strategically co-sponsoring specific bills. However, most junior Senators are building reputation by supporting anything that makes it to the floor. I am going to have to go back and analyze previous sessions to see which approach seems to provide the better payoff.
Relationships by-and-large are unequal between participants. Sometimes they are very close, sometimes they are very different. In our analysis of the Senate, many of these relationships are very unequal; a junior Senator is much more likely to co-sponsor a bill of a senior Senator than vice versa. Without bringing this inequality into play, our notion of network centrality is challenged. In this case, the two Senators most central include one first elected in 2004, followed closely by one who is a member of the powerful Senate Appropriations Committee. If we view networks as expressions of influence over flow of information, including favors, that just doesn’t make sense.
When we start to bring directionality into consideration, which I did by splitting out the sponsors and co-sponsors for half of the Senate’s 104th session (1995); results become much more as expected. The most central Senator was John Warner, then president pro tem.
Your network can help you or work against you, it all depends on the level alignment between your network and your goals. If you are trying to get something done with a team, your network should reflect that. If you are looking for new opportunties, your network should reflect that.
I wrote a short piece for Pollock|Spark about personal networks and suggesting people beginning thinking about the power of networking to help meet their goals.
Every book on sales, finding a new job, etc. stress the importance of networking, and rightly so. While is certainly easier for some than others, the validity to networking is no longer the question. The question you want to ask yourself is: who?
Over our lifetimes of participating with networks ranging from work, to family, to neighborhoods, to hobbies; we accumulate many contacts. There are significantly more effective and efficient ways to spread the word than reaching out to everyone you know, if you know your network.
Let’s go through a few hints, using the image in this article created from my personal email over the past year or so. Click on the image to blow if up larger.
Respect your friends and colleagues. If you abuse their hospitality and trust, not only will you lose them, but you’re also done for.
Don’t spend equal time with everyone. Some people can help you more than others.
If everyone in a group knows each other, only spend time on only a handful of people. When everyone knows each other, the network is dense. Many of the orange and yellow clusters in the image are dense.
Make a special effort with people that connect one or more of your groups.
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.
