Summary. Acquiring accurate context information is crucial to mobile and pervasive computing, and sharing context among nodes enables unique applications. As context information and the applications that consume it become increasingly diverse, they will need an efficient means to indicate tailored interest in this context information. This paper proposes a new probabilistic data structure, spatiotemporal Bloom filters (SpTBF) or "spitty bifs," which allow nodes to efficiently store and share their context interests. SpTBF provide both spatiotemporal locality and a fine-grained ability to control how context interests are disseminated. SpTBF are evaluated by modifying the Grapevine context sharing framework to inform its context dissemination capabilities, and the benefits are characterized in a variety of network scenarios.