Event-based analysis of people's activities and behavior using Flickr and Panoramio geotagged photo collections
Photo-sharing websites such as Flickr and Panoramio contain millions of geo-tagged images contributed by people from all over the world. Characteristics of these data pose new challenges in the domain of spatiotemporal analysis. In this paper, we define several different tasks related to analysis of attractive places, points of interest and comparison of behavioral patterns of different user communities on geo-tagged photo data. We perform analysis and comparison of temporal events, rankings of sightseeing places in a city, and study mobility of people using geo-tagged photos. We take a systematic approach to accomplish these tasks by applying scalable computational techniques, using statistical and data mining algorithms, combined with interactive geo-visualization. We provide exploratory visual analysis environment, which allows the analyst to detect spatial and temporal patterns and extract additional knowledge from large geo-tagged photo collections. We demonstrate our approach by applying the methods to several regions in the world.