Inferring Your Ties on Google Buzz Using What Your Friends Say

A key component of privacy in social networks is the extent to which your connections and associations are public. For instance, Facebook makes your friends' names and IDs available to any application you use, though it allows you some control over how this information is revealed on your profile page. Google Buzz allows you to remove the lists of people you are following and who follow you from your public profile. An interesting question for a Buzz user is how effectively this feature allows you to hide your ties to others from public view.

The graph above shows that in a sample of over seven thousand Google Buzz users, I was able to infer approximately 40% of their ties without needing to refer to their reported ties. I just used the ties their friends reported. With a sufficiently comprehensive crawl, this percentage would approach seventy, or the percentage of people I estimate to make their following and follower lists public.

In other words, in social networks, what your friends say about your ties reveals a lot, even if you yourself keep the information hidden.

How I performed this analysis

Using the student-derived data set I reported on previously, I did the following:

• I collected the follower and following information of 7,225 network participants reporting their following and follower lists publicly.
• I counted a tie when one participant appeared in both the following and follower lists of another participant. This method allowed me to infer when a person who kept their lists hidden was tied to another person.
• For users reporting their ties publicly, I plotted the relationship between inferred and reported ties.
• Regressing reported on inferred ties for these public reporters revealed that for every inferred tie, the person reported approximately 2.5 ties. Stated otherwise, inferred ties represent 40% of reported ties (n.b., 0.4 or 40% is the inverse of 2.5).

That's not the end of it

One might assume that if everyone kept their following and follower lists hidden that that would be the end of it. Well, not really. Ties can simply be inferred based on public communication patterns. The lesson here is that the extent to which any of your interactions take place in a public space, inhabitants of that space will be able to infer things about you and the people you are connected to.

Areas that require further work

As in my prior post, my sampling approach here is not random. In particular, my students were following people who they could find publicly, so the estimate of the percentage of people hiding their following and follower lists is likely low. Further, I'm assuming that people who hide their following and follower lists are similar to those who report them publicly.

The solution to both these issues is better study design with random sampling. Further, the issue of hidden follower and following lists can be addressed by getting those users' permission to access their lists.

 

Do buzz users have more ties than Facebook users? 10,000 answer

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.

Going forward

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.

Future Posts

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.

Hang On: Facebook's Monetizable Assets Are The Connections You Created There

If you examine Facebook's privacy terms (login required), you'll note that you can opt out of sharing almost everything except basic information about who you are and, most importantly, your connections. Connections is a fascinating concept. It includes:

• Your friends.
• Pages you've linked to.

This sounds bad enough, until you read further in the FAQ for this choice quote about how central the notion of connections is to everything you do on Facebook:

Making connections is the main way to express yourself on your profile. Facebook enables you to connect with virtually anyone or anything, from your friends and family to the city you live in to your favorite bands and movies.

Further, as David Recordon, one of Facebook's lead developers states:

The web started as a collection of documents, but people are becoming even more important.

The sum translation of all of these points: The web is no longer about finding things for you. The web is for finding out things about you. You connected to it on Facebook, that must mean you want people to know it about you.

These claims seem outrageous when stated so directly. Why would Facebook make them, albeit not so directly? My bet is that you need look no further than their economics. Holders of ad inventory like Google and Facebook are paid when the ads are clicked. Click through rates on the kind of content ads Facebook shows are 1/10 what they are on the kind of search ads Google shows. Data indicate that Facebook is about on par with Google in terms of number of visitors, at least in the US. Are we to then infer from the click through rates that Facebook revenues are 1/10 those of Google? That might be going a little too far, but it does suggest that Facebook's revenues are vastly inferior to those of Google but likely with similar infrastructure costs given the similar volumes of traffic.

In other words, it sounds like there's a big profit disparity between Facebook and Google.

Big profit disparities are tough for losing competitors to sustain over the long haul and still remain viable. Therefore, Facebook must be looking for an alternative revenue model. One seemingly promising option would be for Facebook to do exactly what it is doing now, leverage the information it has about its users' connections. That information can be used to launch and sustain viral marketing campaigns, something that is really not possible in a search marketing context like Google's. Further, well executed viral campaigns can be highly valuable to companies who will be willing to pay for the wherewithal to conduct them.

Will it work? It's tough to say. People go to a spot like Facebook to socialize, not be marketed to. The beacon controversy of a few years ago suggests that once people see the social space manipulated toward commercial ends, they won't like it any more. It strikes me that this strategy could be a bit of a hail Mary.