Valdis Krebs just wrote a great blog post about his strategy of maximizing his Twitter network efficiency. We all know, the more people you are following on Twitter, the more difficult it gets to keep in touch with all of them. Most often you are reducing your network size by selectively reading about and replying to the people you really care about (the relevant net) or the people you are talking to you (reciprocity).
But if you are looking at your Twitter network as a informational network (and not so much as a relationship network), it is more important how your contacts are related. If you are using your network to keep informed about many different topics, it pays to build a heterogenous network of many people from wholly different areas of expertise. Valdis put it this way:
The trick is to find the people that reach many social circles and follow them. Of course, we need to find more than the minimum of people to follow — you want some redundancy in your network so that there are multiple paths to places of interest for you.
In Social Network Analysis (SNA), there are some ways to put this notion into quantitative metrics. Ron Burt described a measure of redundancy in his greatly acclaimed work on Structural Holes. Stephen Borgatti continued this line of thought and developed a set of metrics to describe redundancy, density and network efficiency. This last measure interested me because it provides a way to measure the effective size of your network - how it would look like without redundant nodes. I’ve written a short function for TwitterFriends to display this measure on the network tab:
After looking at some other Twitter users’ networks, @valdiskrebs’ network efficiency of 95.01% still ranks among the highest values. So, his strategy of building a diverse network that allows for information from different sources to reach him, seems to be quite successful.
To find out your Twitter Network Efficiency, visit this site: http://twitter-friends.com/?user=furukama&mode=net and replace the username with your Twitter username. Maybe the value will seem high at the beginning, but this can be because not all your friends’ connections are in the TwitterFriends database yet. Click on the names below the graphic to load them.