Every time I compile these statistics, I am reminded that one of the best areas of focus for any clever programmer is finding algorithmic ways to handle the immense amount of news that flows through the internet every day. I know there are efforts like APML, etc. to do this, and I wish them every success. I also admire sites like Lifehacker that let you mold their feeds to suit your interests and trim off the stuff you do not want before you ever see it.
Anyway, here I am back with more pointless numbers and graphs. As is often the case, I am reminded of a Dilbert cartoon:
With no further ado, posts marked read per day for the last two months. The time spent away from the internet is over Christmas is readily apparent. The 12/31 spike was logged in less than one hour as I borrowed net access from the kind neighbors, followed by the giant spike once I was home and bailing out from the deluge. The weekend effect remains strong, and the three-day MLK weekend can be spotted, too.
And average posts marked read per day for the last two months. It is no surprise to me that December is down and January up – I suspect that is a holiday artifact and not a trend.
January’s total was 24,109 marked read from 363 feeds – a sick record. The daily max was 2,714, and 11pm is my peak hour with 3,014 (as I save old unread feeds from Google Reader’s data-loss-at-midnight bug). The post-holiday spike also created a false day-of-week max – Thursday with 6,282. Eek! Now that I know about how to get hard numbers from Google’s tallies, I have just a few more charts to show: