Imagine you’re at your local coffee shop, browsing the Internet. You decide to login, and after doing so, you realize you have a new friend request. You don’t know the person, but the face seems familiar. Casually glancing around the coffee shop, you suddenly see the face of the user.
You have just experienced Facebook’s forthcoming algorithm, which will attempt to use patented data mining tools to use location-based resources to connect users who frequently visit the same location.
The plurality of factors can include at least one of an inferred locational proximity between the first user and the second user, a frequency of inferred meetings between the first user and the second user, a duration of each of the inferred meetings between the first user and the second user, or a pattern of occurrences of inferred meetings between the first user and the second user.”
In other words, Facebook will track IP addresses and device signatures on public Wi-Fi networks in order to determine how often two different people are in the same locality and how much time they spend there.
According to the patent, Facebook’s algorithm will employ broadcast triggers that include gyroscopes, accelerometers, and motion processors to track a variety of movements occurring on the Wi-Fi network. These movements include stationary patterns, walking, running, and vehicle-riding.
Facebook describes another example of the algorithm in action: