Your Twitter Feed is a Circle Jerk

If you are like me, then you get most of your ideas from Twitter, and you get most of your ideas while on the toilet.

Pre-IPO, Ben Thompson made the argument that Twitter is valuable not for the product but for its interest graph.

Twitter knows exactly what I like and what I’m interested in. It’s obvious both from what I tweet about, but especially based on who I follow.

I wanted to find out if my interests are really so obvious based on whom I follow.

Several hours later, I made this Twitter network analyzer. It grabs the list of people I’m following and builds a network graph based on whom they follow.

Screen Shot 2015-04-30 at 1.55.22 AM

My Twitter network has a clustering coefficient of 0.133. A network is considered “small-world” if the clustering coefficient is higher than that of a random graph constructed on the same set. A fully-connected graph would have a clustering coefficient of 1.0. Tightly-connected insular networks are bad because they breed confirmation bias. I need a disperse network to introduce new opinions into my brain.

Compare @eiaine with @VCFriendFinder, a Twitter bot that follows every venture capitalist and angel investor it can find. @VCFriendFinder has a clustering coefficient of 0.258. The number is high because investors are are herd animals.

Geez, @pmarca is connected to everybody.
Geez, @pmarca is connected to everybody.

Here’s one for the well-networked @hunterwalk:

Screen Shot 2015-05-01 at 10.20.50 AM

One of my favorite twits, @ritholtz:

Screen Shot 2015-05-01 at 3.29.55 PM

Now go play with it.

This was originally going to be a post about how Twitter shat the bed earlier this week. NASDAQ accidentally posted $TWTR earnings report too soon, and the information leaked all over Twitter itself. I thought that was rather funny, except the stock price crashed 20% before close and shareholders like the ones below are pretty bummed.

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