Privacy Filters and Facebook

In my previous post I used privacy in Facebook as an example of how data filters could work. One point I glossed over was how currently Facebook, indeed all social sites, fail with social distance. Unfortunately, social distance is a necessary for privacy filters to work satisfactorily.

Facebook has one major flaw, once a person is a friend in Facebook they are treated the same as all other contacts whether the connection comes from bumping into the person at a pub or someone you grew up with. It collapses the privacy or social distance between two people. The social distance can be considered how strong the connection between two people is. Social distance provides a measure of both strong and weak ties as articulated by Mark Granovetter.

Without some measure of social distance or strength of connections, any privacy filter is going to fail. The social graph fails to represent the real world connections between people properly.

Facebook attempts to use groupings of friends to approximate social distance but this is cumbersome to use. The manual nature of setting up and categorising everyone into groups is a major barrier to use. People are lazy.

What is needed is an automated method for calculating social distance. Social distance is calculated (and this is how Mark Granovetter categorised connections) by the frequency of communications. Measuring frequency of communications is difficult for Facebook. While Facebook can measure wall posts, internal emails, poking etc., so much more of our communication occurs outside of Facebook, outside of the wall; whether through email, IMs, phone calls, SMS, twitter parties attended etc.; that the frequency of communication within the wall is not a reasonable approximation for the wider frequency of communication.

The key measure of social distance – communication – is hard to quantify as it is dispersed through many different channels. Trying to capture the frequency of communication via porting the data in is one method of dealing with the issue. The other, probably more realistic, method is to start off with some rules and use what can be easily quantified to refine the measure of connection strength overtime.

The rules would look at what is known generically about social connections. Some of rules are:

1. Married is a strong connection
2. The same surname is a strong connection
3. If strong connections to friends with which you have strong connections then you probably have a strong connection

Some of these rules will dictate a very strong connection (first rule) while others will dictate varying strengths dependent on factors such as prior connections with other friends (third rule). All connections start as very weak and are refined first by application of the rules and then overtime by measures of frequency of communication.

Privacy filters all start with knowing the distance between two end points whether physical in case of centuries before or by social distance in the case of today. Until Facebook and any other social-based site has a measure of social distance privacy filters are going to be mediocre at best and more often prone to failure.

Tags: Privacy, Facebook, Filters