Towards integrating real-world spatiotemporal data with social networks

As the popularity of social networks is continuously growing, collected data about online social activities is becoming an important asset enabling many applications such as target advertising, sale promotions, and marketing campaigns. Although most social interactions are recorded through online activities, we believe that social experiences taking place offline in the real physical world are equally if not more important. This paper introduces a geo-social model that derives social activities from the history of people’s movements in the real world, i.e., who has been where and when. In particular, from spatiotemporal histories, we infer real-world co-occurrences- being there at the same time- and then use co-occurrences to quantify social distances between any two persons. We show that straightforward measures either do not scale or may overestimate the strength of social connections by giving too much weight to coincidences