Twitter Fragmentation


It used to be so simple – RT for ReTweet.

If you RT a tweet, it means you agree or “here here.” It is a form of social propagation: I tell two friends, you tell two friends, and so on and so on.

RT became so popular that Twitter eventually added an RT function. Manual RT has the benefit of allowing a comment, but a long RT (160 characters) can’t be fully RT’d manually, because the RTer’s name will take up space thus making the tweet too long. This forces people to edit the tweet before RTing, but that isn’t exactly fair in journalistic terms – a quote is quote even without quotation marks. I have been the victim of such abuse – where an edited RT changed the spirit of what I was really saying.

Fear not, the crowd sourced a new solution: MT.

MT, I thought it was a typo (but the M and R aren’t exactly near each other on the keyboard) stands for Modified Tweet. Or, more precisely a paraphrased RT.

Then there is also HT for Hat Tip or Heard Through. Use HT when it’s basically a new tweet, but the thread, subject, or site in question was discovered via someone else – thus the tip of the hat.

It is nice to see Twitter morphing into a more sophisticated too, but it is also a problem. In this post, GIACSF12, I analyzed an event’s tweets, and trying to figure out what counts as an RT was pretty darn hard. Some started with RT, some inserted the RT in the middle, some used MT, etc. There was no easy way to sort these tweets to count them.

This is an example of The Law of Simple Things. This is one of my famous laws of human nature, a book I am working on that I intend to publish in the afterlife. The Law of Simple things states that many new things attempt to be a simple thing, but if they are successful will evolve into complexity – a law of nature that cannot be controlled or altered. Twitter was as simple as it gets, but it is getting rapidly becoming very complex. It is showing up in the clients and applications, the social protocols, the ridiculous follower count rules, related services such as Klout, and verified user procedures.

Dave Michels