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Subjective logic is a powerful probabilistic logic which is useful to handle data in case of uncertainty. Subjective logic and the Semantic Web can mutually benefit from each other, since subjective logic is useful to handle the inner noisiness of the Semantic Web data, while the Semantic Web offers a means to obtain evidence useful for performing evidential reasoning based on subjective logic. In this chapter we describe three extensions and applications of subjective logic in the Semantic Web, namely: the use of deterministic and probabilistic semantic similarity measures for weighing subjective opinions, a way for accounting for partial observations, and “open world opinion”, i.e. subjective opinions based on Dirichlet processes, which extend multinomial opinions. For each of these extensions, we provide examples and applications to prove their validity.