Evaluation, Orientation, and Action in Interactive StoryTelling

Abstract

Interactive storytelling encompasses a wide variety of applications and systems that aim to allow players in a virtual world to affect the narrative progression prescribed by the author. The story world is often modeled by a set of hand-crafted causal and temporal relationships that define the possible narrative sequences based on the user's actions. In our view, a more promising approach involves applying methods from statistical language processing to create data-driven stories. Here, we explore integrating a typology of narrative clauses from Labov & Waletzky's theory of oral narrative(henceforth L&W) into the Say Anything data-driven storytelling approach. We show that we can automatically distinguish evaluation clauses from orientation and action clauses with 89% accuracy in fables, suggesting that it will be possible to develop new types of data-driven stories using L&W's typology.

M-sense: Modeling Narrative Structure in Short Personal Narratives Using Protagonist’s Mental Representations

“…Previous studies like (Gordon, Bejan, and Sagae 2011) have analyzed personal weblog stories containing everyday situations. Rahimtoroghi et al (Rahimtoroghi et al 2014) and Swanson et al (Swanson et al 2014) used a subset of Labov's categories, including orientation, action, and evaluation in such personal weblog narratives. Black and Wilensky (1979) evaluate the functionality of story grammar in story understanding, As explained earlier, (Papalampidi, Keller, and Lapata 2019)'s dataset for analyzing turning points is a valuable addition in this area of work.…”