Twitter+superscale+survey+by+Rob+Weir

=Twitter superscale survey by Rob Weir=

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=Overview=

In March 2011 Rob Weir plotted and shared graphs of twitter activity.

He wrote: > I’ve been capturing the Twitter Public Timeline since late 2009. I have now nearly 6 million records, each one containing the message, of course, but also the name of the user and their “Followers” and “Following” count at that point in time. I started doing scatter plots of this data and was amazed at the detailed structure evident in the data, that illustrate some interesting ways in which Twitter is being used. No single graph can show it all, so I’m giving you a series of charts, each one showing an area of the Following/Followers phase space 10ox larger.

=Twitter Survey Excerpts=

One Thousand Followers


In this chart each pixel represents one Twitter user, plotted at a position reflecting how many people they are Following, and how many Followers they in turn have. This chart is zoomed in to show only those whose Following/Follower counts are 1000 or fewer.

We see a few trends here. First, there is a predominance of users with counts less than 300 or so. But we also see a strong trend toward parity in counts. That is the line going up to the right at 45 degrees. This would be expected for socially-interacting groups of mutual followers.

What I did not expect were the “spikes” for users who follow 100, 200 and 300 accounts. This is not an aliasing artifact of the graphing. This is real. Is there something out there that would lead large numbers of users to follow exactly 100, 200 or 300 users?

(For those of you interested in how the chart was created, I used alpha blending to deal with the “overplotting” problem. So each point is plotted in a partially transparent way, so an area gets darker the greater the density of points.  If I didn’t do that, the entire chart would be one giant blot of black, with no discernible patterns.   I also introduced random “jitter” between -0.5 and 0.5 to avoid false patterns caused by integer quantization interacting with screen resolution.)

Ten Thousand Followers


Moving out a factor of ten, we now look at those users who have 10,000 or fewer followers. Again, each pixel represents one sampled user. The entire previous chart would fit in to the lower left corner.

The salient feature here is the hard cut-off at 2000. This is due to Twitter’s “aggressive following” limitation: “Once you’ve followed 2000 users, there are limits to the number of additional users you can follow: this limit is different for every user and is based on your ratio of followers to following.”  They are a bit coy about what exactly the rule is, but a look at the chart certainly suggests that having a Following/Followers ratio > 1 is going to be a problem.

We also see an unexplained density of people Following exactly 1000 users.

One Hundred Thousand Followers


Another factor of 10 and we switch to a different presentation, representing users with small circles rather than pixels. We’re now starting to see recognizable users and information sources. I’m illustrating some account names at random. Maybe not exactly celebrities, but there are some broadly followed users here. Since the only way to follow 100,000 users is to have close to that number already following you, the lower right half of the chart is empty, and will remain so as we continue to zoom out.

The structure here seems to be:


 * Information pushers who follow nearly no one, up the y-axis on the left.
 * Users who follow almost everyone who follows them, running diagonally
 * Nothing much in the middle

One Million Followers


Zooming out another factor of 10, and we see that the Following count trails off. Does Twitter have another limit here? Or do people realize that it is pointless to follow 500,000 people? But why wouldn’t they also see that it is senseless to follow 50,000 people?

Ten Million Followers


And in the last chart we take it out one more order of magnitude, and the Twitterverse recedes to be Ellen DeGeneres, Britney Speaks, Barak Obama, Justin Bieber and Ashton Kutcher. If you are an average Twitter user, like me, everyone you know and actually interact with on Twitter is represented by 1/20th of a pixel in the lower left corner of the chart.

Note that this chart (and the previous) one do not reflect the current Follower/Following count for these particular users. This is not a concurrent snapshot. This was all sampled over an 18 month period of time. Different users are necessarily shown according to their status at different dates. The point is to show the structure of the data, not make a claim that, e.g., Ellen DeGeneres has more followers than Justin Bieber.

=Links=

@http://www.robweir.com/blog/2011/03/twitter-powers-of-ten.html. This work, unless otherwise expressly stated, is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.