The affective profiles model (i.e., four possible profiles based on the combination of people’s high/low positive/ negative affect) has led to a great number of studies on individual differences during the past ten years. Nevertheless, only a handful of these studies have investigated actual behavior. Here we put forward two ways for analyzing online behavior (i.e., Facebook status updates) using data published elsewhere. We used the affective profiles model as the framework to investigate individual differences in the words people use when they write on Facebook and the semantic content of their status updates. We suggest that the use of computerized methods to quantify and analyze text need to be used in order to move the affective profiles model into the era of big text data.