Story understanding is a notoriously difficult problem in AI. Broad-spectrum, common-sense knowledge about the world is a good resource, but current common-sense knowledge bases are far from human-level story understanding. We examine affective story understanding in order to perceive the broad emotional overtones of a story at the sentence level, using both a common-sense perspective and the observation that much of the way we emote in response to everyday situations is part of a shared human experience and therefore a part of common sense. With a corpus of common-sense knowledge, we create a semantic network of everyday situations and the emotions associated with them, which, when combined with our linguistic processing, lets our system classify story sentences into six primitive emotions. We then explore how this technology enables innovations in emotional UIs such as EmpathyBuddy, or in prosody, emotional TTS, gaming, story evaluation, and emotional indexing of documents.