Effective Scenario Designs for Free-Text Interactive Fiction
Free-text interactive fiction allows players to narrate the actions of protagonists via natural language input, which are automatically directed to appropriate storyline outcomes using natural language processing techniques. We describe an authoring platform called the Data-driven Interactive Narrative Engine (DINE), which supports free-text interactive fiction by connecting player input to authored outcomes using unsupervised text classification techniques based on text corpus statistics. We hypothesize that the coherence of the interaction, as judged by the players of a DINE scenario, is dependent on specific design choices made by the author. We describe three empirical experiments with crowdsourced subjects to investigate how authoring choices impacted the coherence of the interaction, finding that scenario design and writing style can predict significant differences.
This material is based upon work supported by the National Science Foundation under Grant No. 1560426. The projects or efforts depicted were or are sponsored by the U.S. Army. The content or information presented does not necessarily reflect the position or the policy of the Government, and no official endorsement should be inferred.
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