GeoEcho: Inferring user interests from geotag reports in network traffic

Being transmitted as part of numerous Internet services, geo location data is increasingly bringing hints of people's real-world activities into Internet traffic. This paper focuses on the discovery of key properties that motivate personal activities - locational interests. We propose and design GeoEcho, a mobile traffic analysis system that extracts and analyses a wealth of latitude-longitude geotag reports with the purpose of identifying the points of interest (PoI) which people actually visit. The key challenge in such identification is that geotag reports are commonly sent arbitrarily, sparsely and without a sufficient accuracy to uniquely identify any PoI. In our analysis of a two-week trace from a large North-American cell phone operator, we show that 22[%] of geo reports do not even represent actual people's positions, while another 45[%] of the reports have low accuracy, such that they ambiguously indicate a number of potential PoIs. We devise methods that effectively identify and prune irrelevant geo information and infer personal interests of individuals. Thereby creating representative profiles of personal interests, our key results reveal that users show interest in a limited number of topics, and their interests are largely unique and stable over time. Our analysis shows a significant GeoEcho usability in various contexts ranging from generic user profile and user group analysis, to advertising and security applications.