Word of Tweets
Tuesday, March 9, 2010 at 12:38AM Discovering information on the internet has evolved throughout the years. As we've hit a point where information is pushed on us in near real-time, discovery and curation have become more important than ever.
At one point in the history of the internet, websites were discovered through word of mouth. Your friend, family member, coworker, told you about some great thing at "http://" that he or she heard about. Word of mouth expanded its reach, and medium to passing links on through email and websites, curating links for users.
Then came along RSS, allowing you to subscribe to your favorite and or trusted sources. This allowed information to flow to you automatically, as well as a greater influence and understanding of trending topics from the website author's perspective.
Del.icio.us offered interesting view on information, providing the ability to view what everyone is bookmarking, sharing your bookmark, or to even view what bookmarks are available on a given topic. For myself, Delicious has become an invaluable research tool.
Digg changed the game on how information is curated. Digg allowed its users to submit, vote, and comment on articles, making it a fully community driven news source. Voting and commenting added an "interesting" factor to any story.
As of lately, Twitter, has become my source of trending topics, alongside Digg, and my RSS feed subscribing to a small list of blogs I enjoy reading. With Twitter, you have several streams of tweets. Public tweets that are sample of what the Twitter community is chirping about. Lists which enable you to curate based on a topic, and of course your following list, which are individuals you want to always to see tweets from.
Like many services, Twitter publishes an API for developers to leverage in their own applications. One such API allows an application to sample tweets using an algorithm Twitter has decided on. Over a day, I managed to capture 1,331,214 tweets, a small percentage of overall tweets per day, but enough to run basic analysis against.
Of those 1.3 million tweets, 21% contained links to websites.
With 21% of tweets containing links, you stand a fair chance of discovering some tidbit of information out there. More importantly though, is the link interesting, and does the Twitter community find it interesting by retweeting it.
As expected, majority of the links were shortened using a service like bit.ly.
Expanding the URLs took a bit of time, but allowed for comparisons and uniqueness across the sampled set. Pictures, videos, location were the top links. URL4.eu is a flaw in the analysis tool as URL4 proxies content through its service instead of just redirecting like other shorteners.
In the sample tweet data set, majority of the links, about 99%, only occurred once. There were some that occurred 20 to 40 times, a handful more than that. One occurred 1500 times, a link to LilTwistTV on UStream.com. Now all the tweets did not occur at once, but over a fourteen hour period, slowing tailing off at the end.
This is no different behavior than any hot topic in a community, without the location barriers. A similar trend can be seen at a smaller scale for a MacHeist promotion.
While I was reviewing a sampled data set, the full stream of tweets would either amplified this trend, or at a minimum resulted in the same number as in the sample. Whether you are a fan of LilTwistTV or not, the frequent retweeting increases its network, and visibility to you.
Twitter is now word of mouth.

