Category Archives: Facebook

Does Facebook leak what profiles you click on?

Check out Preview My Profile on Facebook:

Account (top right) > Privacy Settings >

Customize Settings > Preview My Profile

Now say you have a friend named Bob. Type ‘Bob’ in the box at the top of Preview My Profile to see how your profile will be seen by him. Take a look at the Mutual Friends section (bottom left in the screenshot above) of your profile (from Bob’s view – so still in Preview My Profile). Notice how these mutual friends seem to bias towards those who are closest to Bob (and perhaps to you as well). This by itself is pretty interesting. I can see who my friends are closer to relative to our other mutual friends. This pattern seems to hold up well in my trials over my friends who I know well (I saw that their closest friends were popping up more often than not in the mutual friends section).

This got me curious about how Facebook determines “closeness” between two people. In particular, does Facebook leverage your clicks on a friend’s profile in determining how close you are to that friend? To experiment, I frequently clicked on my friend’s (say her name is Alice) profile and newsfeed updates over two weeks. She’s someone I rarely communicate with. I then normally browsed profiles of mutual friends I share with Alice and noticed that in the mutual friends section of those profiles Alice frequently showed up (even when the total number of mutual friends was greater than 80 – keep in mind that the mutual friends section only shows 3 friends). Now, there’s definitely randomness at times and I believe multiple ranking features are probably being used here (like perhaps number of exchanged messages) but I have a feeling clicks might be in play here as well based on this result.

If Preview My Profile gives you the same view over mutual friends as what you see normally when you click on a friend’s profile, and if mutual friends uses private information like clicks / messages as features in the ranking, then it may be possible to infer who your friends are communicating with or clicking on more – or at the very least, find who they are closer to relative to your other mutual friends. If I view my profile from Bob’s eyes and frequently see Alice appear in the Mutual Friends section over multiple runs it may imply a strong relationship from Bob to Alice. Also, when the number of mutual friends is high relative to the number of total friends your friend has, then this result may be even more accurate.

This isn’t scientific by any means – I really don’t know how the ranking is done and may be completely wrong – so take it with a grain of salt. Just thought it was an interesting feature and pattern worth sharing …

Advertisements

1 Comment

Filed under Blog Stuff, Facebook, Non-Technical-Read, Social

Is the Facebook Application Platform Fair?

Take a look at this stats deck from O’Reilly’s Graphing Social Patterns conference:

http://en.oreilly.com/gspeast2008/public/asset/attachment/2950

Fairly in-depth and recent [6/01/2008] analysis of the application usage in Facebook and MySpace.

As expected, lots of power law behavior.

I found the slides describing churn to be pretty interesting. Since October 2007, nine of the top fifteen most popular applications are new. However, only three of those new applications debuted after March 2008. I expect the amount of churn in the top spots to continue to drop based on the recent declining active usage trends and Facebook’s efforts to curb application spam (new UI that puts applications in a separate profile tab, app module minimizing, viral friend messaging limits, security compliance, etc).

What I would find even more interesting is a study of the number of applications users install, and how those moving averages have changed over time. Like say the number of applications a typical user installs is 4. Once the user reaches that threshold, what’s the churn like then? Specifically, what are the chances that a user will add a new app? Or maybe an even better metric: how long does it take, and how does this length of time compare to when the user had 1 app and increased to 2, or 2 apps and increased to 3, etc.? Basically, what’s the adoption rate/times based on current application counts?

I believe it becomes harder to influence a user to add or replace for a new app if the number of current apps the user has is high. I think most users, without even knowing it, have a threshold of how many total apps they are willing display on their profile – and that this threshold is based on an ongoing evaluation of the utility and efficiency of the page. Each app takes up real estate on the profile page, and a “rational” user will only show so many until page load times degrade and/or core modules (wall, general information, albums, networks) get drowned in clutter and thus become difficult for users to locate. Of course, social networks like MySpace which have very minimal profile page design constraints prove that most users are irrational 😉 – but it’s this design control that greatly helped Facebook dominate the market IMO.

If this is true, then it means that first movers really, really win in the Facebook apps world. Companies like Slide and Rockyou manage many of the top applications, and given the power law market share phenomena, they control a majority stake of application usage and installs. Many of these companies had the early bird advantage, and once winners, always winners – acquisitions of emerging applications, leveraging branding and existing audiences (a.k.a monopoly) to cross promote potentially copy-cat applications faster and wider than the competition, etc. Monopolies inside Facebook have unsettling ramifications, as they block newcomers from capturing profile space. If they fail to innovate (as most monopolies) then next-gen application development may never get through.

Now, if users do have an application count threshold, and it becomes successively more difficult to replace/add a new app as this count increases, then any apps developed now have a substantially rarer chance of gaining market share. If winner’s win, first movers reap, and churn becomes improbable over time, then the early top apps have already most likely filled up users’ allocated app slots.

I find thinking of the profile page as a resource allocation problem rather fascinating. Essentially, there are finite resources on a page and we expect rational users to perform some optimization to allocate resources to maximize utility for themselves and for others (potential game theory link). Once users fill up these resources, human laziness kicks in. Another warrant for improbable churn is that users who want to add new applications after filling up their resource limit will need to remove an existing app to make space. The standards for change are higher now, as the user must compare the new app to an existing preferred app (which probably is a popular early-bird app that friends use), and so the decision will incur a trade-off.

One could also argue that with more apps available now (second slide shows that despite sluggish usage the # of app’s being developed is still growing insanely) users are burdened with more choices. Or, one could argue because most users have reached their app limit, and thus, churn has become improbable, the discoverability of new apps among friends (a critical channel for adoption) also becomes improbable.

Under this theory, especially in context of Facebook’s current efforts and app stats, the growth of new app adoption in social networks will continue to slow down.

So what can be done here?

The platform needs to encourage more churn by building a fairer market that matches users to high quality apps that satisfy their expressed intents. At the end of the day, these applications are really just web pages, but unlike the web, they do not leverage important primitives like linking and meta tags. Search engines like Google and Yahoo use these features extensively to calculate authority and relevance. In the long run, as the number of sources increases, advanced ranking algorithms and marketplaces are necessary to scale and ensure fairness to worthy tail publishers. Maybe social networks should inherit these system properties to bolster their tail applications.

Also, Facebook needs to encourage users to variate or add more applications to their profile page. Facebook’s move to put applications in its own profile tab may very well achieve this goal, but at a consequence of lowering their visibility.

Anyways, just some random thoughts about the current state of Facebook apps. It’ll be very interesting to see how their platform progresses and how it will be perceived by end users and developers in the future.

3 Comments

Filed under Economics, Facebook, Non-Technical-Read, Social, Statistics, Trends