Analyzing large volumes of big geo‐data through social sensing provides new research opportunities in urban studies. Such big geo‐data include mobile phone records, social media posts, vehicle trajectories, and street view images. They can be used to extract human behavior patterns and infer the geographical characteristics of cities. This chapter discusses a number of analytical methods for big geo‐data in social sensing studies, such as temporal signature analysis, text analysis, and image analysis. These methods can be used for various applications such as estimating urban vibrancy, formalizing place semantics, and modeling intraurban human mobility patterns. We structure the chapter sections from a perspective of first‐ and second‐order properties in spatial statistics .