Extending the h-index to Twitter

May 28, 2009

by startupmarketingdiva

Recently, I became a Tweeter.   Cool stuff.  And being the quintessential scientist that I am – a practitioner of the scientific method and strong inference, I like to collect and analyze data.  So, I began thinking about Twitter metrics and analytics.

Here are the basic key Twitter metrics to consider:  Number of followers, number following, number of updates, number of @replies, and number of @RT (i.e. “ReTweets”).  I found this last one to be the most intriguing especially after reading The Genius Index: One Scientist’s Crusade to Rewrite Reputation Rules in this month’s issue of Wired Magazine.  In a nutshell, this article is about Jorge Hirsch, a physicist who lives in a world defined by the “publish or perish” mantra, who decides to re-write the algorithm that defines a scientist’s reputation.  It’s not just about the journal impact factor (i.e. the caliber of journal that a scientist’s research is published in), but rather how many times a scientist’s work is cited by other researchers.  This is referred to the h-index (aka “the hirsch index” of course).

Similarly, it’s almost meaningless to note how many followers you have on Twitter.  Because, sooner or later, you’re going to get bots and spammers following you as well.  Plus, some Tweeters follow simply so that you can turn around and follow them – a kind of a diplomatic gesture, I suppose, in the Twitter world.  But, when a Tweet is ReTweeted, that’s when the signal to noise ratio increases for that particular Tweet and Tweeter.

There are groups working on a number of other metrics for Twitter – check out TwInfluence, which is a site where you can measure your influence as a Twitterer.  I don’t know the actual algorithm, but it calculates your degree of influence based on the velocity at which you acquire followers, taking into account their degree of influence, and the number of followers you accumulate over time, among many other metrics.  And, just today, I came across a search engine built especially for the social web called TOPSY (in the interest of full disclosure, one of the founders is my cousin).  It seems that TOPSY’s value is that it returns information in real time and more importantly, it filters the signal from the noise by using  reputation as a key metric.  So, for example, on Twitter, it filters the Tweets (and the links in the Tweets) that are most valuable based on the reputation of the author.  So your search returns information in the context of what people are actually talking about.

There’s a lot going on.  The dust storm is just starting and it’ll be a while before it settles.  But, like the early days of the internet, when the ‘hit counter’ ruled, similarly, in these early days of Twitter, ReTweets are a key metric to consider, or so it seems.

I’d like to hear your comments.  Yours truly – startupmarketingdiva.  Follow me on Twitter @startupmktgdiva.

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One Response to “Extending the h-index to Twitter”

  1. Joseph Young Says:

    Interesting post startupmarketingdiva,

    I think another important metric to measure is hashtag frequency. This is tag that CNN is targeting for the current Iranian election crisis. I think it’s amazing how social media has become the leader in realtime news coverage. Watching the events unfold on CNN illustrated how reports used Twitter as a first hand source, while admitting possible errors in the source. With the addition of video recording on the iPhone 3GS, the next incident may be broadcast from a Twitter Video service.


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