This dissertation studies how people describe emotions with language and how computers can simulate this descriptive behavior. Although many non-human animals can express their current emotions as social signals, only humans can communicate about emotions symbolically. This symbolic communication of emotion allows us to talk about emotions that we may not currently be feeling, for example describing emotions that occurred in the past, gossiping about the emotions of others, and reasoning about emotions hypothetically. Another feature of this descriptive behavior is that we talk about emotions as if they were discrete entities, even though we may not always have necessary and sufficient observational cues to distinguish one emotion from another, or even to say what is and is not an emotion. This motivates us to focus on aspects of meaning that are learned primarily through language interaction rather than by observations through the senses. To capture these intuitions about how people describe emotions, we propose the following thesis: natural language descriptions of emotion are definite descriptions that refer to intersubjective theoretical entities. We support our thesis using theoretical, experimental, computational results. The theoretical arguments use Russell's notion of definite descriptions, Carnap's notion of theoretical entities, the question-asking period in child language acquisition, and Socratic epistemology. The experimental data we collected include dialogs between humans and computers and web-based surveys, both using crowd-sourcing on Amazon Mechanical Turk. The computational models include a dialog agent based on sequential Bayesian belief update within a generalized pushdown transducer, as well as a fuzzy logic model of similarity and subsethood between emotion terms. For future work, we propose a research agenda that includes a continuation of work on the emotion domain as well as new work on other domains where subjective descriptions are established through natural language communication. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]