
Nathan Yau, the guy over at Flowing Data (an amazing blog), recently posted about a website called tweetolife that allowed you visualize tweets by either gender or by hours. So for instance a simple check on the word ‘shopping’ allows you to see what words were most associated with shopping on every tweet sectioned out by gender. For instance Men are more likely to tweet about shopping portals, or amazon or cash. While women are more likely to tweet about dresses or their parents (weird!). The data itself isn’t complete but it does let you kill about 10 minutes of your time trying to figure out the twitter universe. I had a fun time looking at the differences between men and women, confirming my suspicions and creating doubt in some others.








