Chimera supports authoring narratives of group membership in any social identity domain through a data-driven approach. It models identities (avatars, characters, profiles, and accounts) in two primary ways: (1) by modeling the underlying structure of social categories and related phenomena with the Chimeria engine, which mathematically models users’ degrees of membership across multiple categories; and (2) by enabling users to build their own creative applications involving social characterization, such as videogames and social media.
Important models are those of category membership and naturalization trajectories. In modeling categories, Chimera develops and implements a notion of abstract and concrete categories that can encompass multiple worldviews. To computationally model category gradience, Chimeria computes a closeness value corresponding to the degree to which an actor deviates from a prototypical member of a category, who is defined via a set of features. The degree of membership fluctuates throughout a narrative by actions and choices made by the user. Attributes are added/removed for discrete features (e.g. acquired skillsets) or modified numerically for continuous features (e.g. height), which creates fluctuating degree of membership and naturalization trajectory for the user.