Abstract
Social media (such as Twitter, Instagram, and Facebook) are powerful computer‐supported social networks for idea exchange and personal networking. Most social media messages contain spatial information in the form of geotags, user profiles, or place names in the messages, which can be used to create spatial social networks. Spatial social networks transform social networks into maps and information landscapes using real‐world locations or abstract coordinate systems. After the transformation, scientists can conduct space–time analyses, understand the diffusion of information, and identify spatial cluster patterns of network elements. Scientists now can trace, monitor, and analyze the dynamic change of social networks and social communications from a perspective of spatiotemporal analysis. These research efforts can help us understand the characteristics of innovation diffusion, enable the discovery of knowledge in cyberspace, and facilitate the emergence of a data‐driven computational social science.
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