The
URLs Light dataset, which we have released, and the much larger
URLs Full Dataset, which will be on its way soon, are protected by the principles of "differential privacy". We implemented differential privacy by adding specially calibrated noise to each dataset. The noise guarantees that individuals who may be represented in the data cannot be reidentified, and any clicks, shares, or others actions cannot be associated with any one person. Despite the noise, differential privacy makes it possible for statistical analysts to learn social science patterns from the...
Read more about Analyzing Data From Facebook