Abstract Social sensing has emerged as a new paradigm of growing interests, where individuals volunteer (or are recruited to) collect and share observations or measurements about the physical world. This opens up unprecedented opportunities and challenges centered on Big Data processing and information distillation in social sensing, where the goal is to distill accurate and credible information from large amounts of unfiltered, unstructured, and unvetted data generated by social sources (e.g., humans or devices on their behalf). Achieving this goal requires multidisciplinary solutions that combine data mining, cyber-physical computing, network science, and statistics. The proliferation of sensors in the possession of the average individual,

of online media (e.g., Facebook and Twitter), heralds era of Big Data in social sensing that brings together new research challenges reviewed in this chapter.