Shortened Barack Obama links to The Sun, Guardian

A quick visit brings up the front page of British tabloid The Sun.

Sun from Obama

That web address is what calls a “custom alias.” It works great when I wan to tell someone where to find my Google profile: That’s much easior to remember than, or a cryptic address that most URL-shortening services produce.

But you don’t have to be the new president to create a shortened address that contains “Barack” or “Obama.” points to a November blog post on about efforts to trademark the then-president-elect’s name: Barack articleAnd here are some other shortened URLs that contain the president’s name, along with the pages they point to. did not make the list because terminated the address. TinyURL says the address was “used by its creator in violation of our terms of use.”

Thank you to for expanding all of the shortened web addresses mentioned in this post.

Over half of Obama tweets contain links

Late last week, I noticed many of the tweets on Twitter’s Election 2008 page contained links. A screen grab taken this morning shows that still to be the case almost one week after Election Day.

As a matter of fact, 355 of the last 500 tweets that contain “obama” also  include a link (as of about half an hour ago).

I created a Yahoo! Pipe to search Twitter for the last 500 words containing a keyword on a particular date. The pipe takes those items and returns a list of those that include “http://” — the items that contain links.

After seeing that Obama was tweeted 109 times per minute on Election Day, I decided to run both then-presidential candidates through the Pipe. I was surprised to find that less than 25% of the tweets on Tuesday contained links: 89 of 500 Obama tweets, and 109 of the same number of McCain tweets.

So I ran the numbers for the first seven days of the month. About half of the tweets about either candidate included links everyday except Monday and Tuesday.

Compare that to the volume of tweets (from my previous post), and it looks like the more people tweeted, the less likely they were to include links.

Tomorrow, I’ll show how these numbers compare to other popular Twitter search terms and all tweets in general.

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Obama was tweeted 109 times per minute

In the span of four minutes and 36 seconds, 500 messages containing the word “Obama” were posted to Twitter on the afternoon of Election Day. The flurry started 27 seconds after 3:55 p.m. PST, when a livejournal blogger from Kentucky posted this simple tweet: “Obama 08!

During that time, an average of 108.7 Obama tweets were published every minute.

What about Senator McCain?  Starting at 3:50 p.m. that day, an average of 50 messages with the word “McCain” appeared on Twitter every minute. There were 500 McCain tweets in the span of ten minutes.

Last week’s Twitter traffic for both candidates peaked on Tuesday, but I suspect the high water mark was set sometime during or after the president-elect’s acceptance speech. Unfortunately, I am unable to identify the peak hour and/or minute of traffic.

I’m working now on a post that will tie the Twitter activity to the main topic of this blog: the almighty (hyper)link. 

In the meantime, I just want to share these numbers and my methodology, with the hope that a bored programmer wil figure out what time the Obama Twitter traffic peaked.

Trust me, if you aren’t a statistician or programmer, you should stop reading now!

My methodology

  1. Use the Twitter Search API to retrieve the last tweets that contain a keyword on a given date.
  2. Use Yahoo Pipes to aggregate five pages of results. The Twitter Search API returns a maximum of 100 tweets per page. Aggregating will create a feed with 500 tweets.
  3. Use Pipes to sort the feed chronologically.
  4. Still in Pipes, create a new feed that contains only two items: the most recent post from the original feed, and the oldest post.
  5. Rename the title of each post to reflect its timestamp (measured in seconds). 
  6. Calculate the “elapsed time” by taking the difference of the two timestamps.
  7. Divide 500 (the number of tweets) by the elapsed time. This is the number of tweets per second.
  8. Multiply the number of tweets per second by 60 (the number of seconds in a minute) to arrive at the number of tweets per minute.

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