Computationally Modeling Narratives of Social Group Membership with the Chimeria System

Narratives are often used to form, convey, and reinforce memberships in social groups. Our system, called Chimeria, implements a model of social group membership. Here, we report upon the Chimeria Social Narrative Interface (Chimeria-SN), a component of the Chimeria system, that conveys this model to users through narrative. This component is grounded in a sociolinguistics model of conversational narrative, with some adaptations and extensions in order for it to be applied to an interactive social networking domain. One eventual goal of this work is to be able to extrapolate social group membership by analyzing narratives in social networks; this paper deals with the inverse of that problem, namely, synthesizing narratives from a model of social group membership dynamics

A Narrative Sentence Planner and Structurer for Domain Independent, Parameterizable Storytelling

Storytelling is an integral part of daily life and a key part of how we share information and connect with others. The ability to use Natural Language Generation (NLG) to produce stories that are tailored and adapted to the individual reader could have large impact in many different applications. However, one reason that this has not become a reality to date is the NLG story gap, a disconnect between the plan-type representations that story generation engines produce, and the linguistic representations needed by NLG engines. Here we describe Fabula Tales, a storytelling system supporting both story generation and NLG. With manual annotation of texts from existing stories using an intuitive user interface, Fabula Tales automatically extracts the underlying story representation and its accompanying syntactically grounded representation. Narratological and sentence planning parameters are applied to these structures to generate different versions of the story. We show how our storytelling system can alter the story at the sentence level, as well as the discourse level. We also show that our approach can be applied to different kinds of stories by testing our approach on both Aesop’s Fables and first-person blogs posted on social media. The content and genre of such stories varies widely, supporting our claim that our approach is general and domain independent. We then conduct several user studies to evaluate the generated story variations and show that Fabula Tales’ automatically produced variations are perceived as more immediate, interesting, and correct, and are preferred to a baseline generation system that does not use narrative parameters