Online social networking and information sharing services have generated large volumes of spatio-temporal footprints, which are potentially a valuable source of knowledge about the physical environment and social phenomena. Meanwhile it is critical to understand the uneven distribution of the data generated in social media in order to understand the nature of such data and to use them appropriately. Using georeferenced tweets and photos collected from Twitter and Flickr, I will present the spatial and temporal patterns of such crowd-sourced geographic data and explore the socioeconomic characteristics of geographic data creators. This type of research would be important to business researchers who intend to understand the influence of social media, sociologists who study the behaviors of social media users, geographers who are interested in the spatial and temporal distributions of crowd-sourced information, and other scientists who use social media data in their research.