The graph above is based on an analysis of 10,113 buzz users where 7,225 of them chose to share their "following" and "follwers" lists publicly. In the graph, I'm counting Buzz user ties as occurring when two users each follow the other. In other networks, like Facebook, ties are equivalent to friend relationships between users.
The distribution of ties is quite clearly skewed to the left:
- The maximum number of ties recorded for any one user is 4,754.
- However, the vast bulk (90%) of users have 394 ties or less.
- 76% of users have the mean number of ties (159) or less.
- The median user (the user at the half way point in the list) has 50 ties.
- In other words, half the users on buzz have 50 ties or less.
So, do Buzz users have more ties than Facebook users?
As of today (8/12/2010), the average Facebook user has 130 friends. If we look at the mean number of ties for a buzz user in this sample, 159, then buzz has a slight edge but is clearly in the same ballpark.
In the case of either buzz or Facebook, we have to recognize that the ties are nominal. The level of ties actually maintained on either network is likely just a fraction of the nominal number as suggested by an in-house analysis done by Facebook.
How I collected the buzz data (why you should take this with a grain of salt)
The data is based on a snowball sample originating with myself and my 10 web marketing practicum students. I then went to the friends and finally to the friends-of-friends levels. The data were collected from August 4 to August 5, 2010. Here is a summary of the number of users analyzed at each level:
- Core group (myself + students): 11
- Friends: 161
- Friends of friends: 9,941
A few points about this sample:
- The students all have fewer than the median number of ties. While I have over 100 or double the median publicly reported.
- In other words, all of the outliers with many ties come from the Friends and Friends of friends levels.
This latter illustrates the problem with snowball sampling. It's hard to know what aspect of it is representative of the population as a whole. A random sample would alleviate this problem.
I began down this path in an attempt to keep track of the networks my students were forming as we proceeded through the semester. The area that interests me most is the quality of ties they are forming. Going forward, I'm most likely to push on content analysis and network structure.
The mathematically inclined will have already noticed that 29% of my sample did not want to share their following and followers lists publicly. I'll be providing more analysis on this group in a future post.