This week I asked if you were interested in statistics as they related to Twitter. I should have asked if everyone answering the emails were breathing, the results would have been the same, 100%.
Everyone seems to be interested in Twitter. But even more, they are interested in statistics on just about anything. People love to know the numbers. How fast, how slow, how many, how much, who is the best, who is the worst? For some reason we are fascinated by this type of thing. It does not seem to matter if it is Twitter or thoroughbreds, if people think they may profit from knowing, they want raw numbers.
I was at 140tc last week, The Twitter conference in Mountain View. The top presentation was from @Al3x concerning the Twitter API. But a close second was a panel where statistics were presented. There were statistics concerning Re-Tweetability, Contribution, Community Standing, Strength of Followers. If you could place an number on it someone was reporting on it. I want to spend a little time on some applications I saw.
First Twitalizer. This group leverages statistics to produce the value of contributors on Twitter. Twitalizer fits Twitter statistics into the neat boxes of Influence, Generosity, Signal, Velocity and Clout. The boxes are defined by Twitalizer, but the data is derived from Twitter. They have a good idea, I am not sure that I want this to determine who is the most influential Twitter user. It will not take long, as Google found out, for the SEO community to form an secret army that follows,unfollows and Tweets in mass so they may game the system. Twitalizer stressed a couple of times that they were not "Google for Twitter", but I could not help notice that @Scobleizer and @GuyKawasaki stats looked a lot like Walmart and CitiGroup page rankings. It will be interesting to see how this site moves forward.
Next we looked at
TwitterStats. This appears to be a more than a single application, one to check your TweetStats, others to compare your stats with everyone else. The creator,
Damon Cortesi, is more than happy to share his view on statistics. That's a good thing, Damon is one of those people that loves to dig through the numbers to uncover a hidden gem of a fact. Damon has some really cool graphs to measure exactly how often and in what volume you Tweet. One of the moe interesting statistics he has, in my opinion, is the measurement of who you are retweeting. In other words are you simply rebroadcasting the same person over and over? I was surprised at my results, and no, it was not Scobleizer!
Finally a gentleman named
Dan Zarrella presented his efforts. He also is interested in the "retweetability" factor, but from the other side of the mirror. Dan takes a look at users that are being retweeted and uses math to come up with a number that defines their propensity to be retweeted. Dan refers to this quality as their "infectious power" of their Tweets. Dan describes himself as a social media scientist, I agree. I spoke with him briefly after his presentation at 140tc and it was like talking to a young Oppenheimer of the social media rat pack.
There are many more initiatives working to produce statistics on Twitter. Even here at Pervasive we have leveraged some
hyper-parallel threading software to comb through the massive feed at Twitter. One of our early experiments is focused on extracting the signal from all the noise. We took the feed and looked within it to find people talking about two items, "Austin" and "SXSW". Easy enough, we could have accomplished that with Twitter search, but what we really wanted to know was not only who was talking, but when they were talking. We took the results and compiled them into 24 bars on a chart, each representing an hour of the day. We made the bars drill down capable, so now we not only knew who, and when, we can also see exactly what was said.
Twitter has a lot of buzz right now, but I think analytics and statistics are what are really going to be the buzz for the coming years. There is more and more data being created everyday. Mixing that data and extracting meaningful information is the next big thing. Look at the push behind Web 3.0 and other initiatives focused on the data. Even at Twitter, that team is more focused on the content then the number of users generating it than ever. I predict that a new wave of statiscal and analytical applications will be published this year that will view data in a whole new way.
This Weeks @BJacaruso One Question Survey
Beyond the data and content their is the idea of delivery. Was thinking about how iPhone says "there's an app for everything." Made me wonder how many are using the phone (i or otherwise) to do business.
Do you use your phone to access business applications?