Suspense is an important emotion for the enjoyment of games. Various methods have been proposed to manage suspense in games. Most existing works focus on managing suspense via storytelling or artifacts, such as sound effects. However, little work has been done in studying how to use gameplay to manage suspense. In this paper, we present a study in which we developed a horror-adventure game with a built-in suspense manager based on adaptive gameplay. We conducted a small user study to evaluate the effect of dynamic suspense management on game players. Our results showed that gameplay could potentially be used to manage the level of suspense experienced by players, independent of the story and artifacts in the game. The work discussed in this paper will provide game designers with new tools for suspense management in non-narrative-based games.
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A Computational Model of Suspense for Non-Narrative Gameplay
In recent years, various mechanisms have been proposed
to optimize players’ emotional experience. In this paper,
we focus on suspense, one of the key emotions in gameplay. Most
previous research on suspense management in games focused on
narratives. Instead, we propose a new computational model of
Suspense for Non-Narrative Gameplay (SNNG). SNNG is built
around a Player Suspense Model (PSM) with three key factors:
hope, fear, and uncertainty. These three factors are modeled as
three sensors that can be triggered by particular game objects
(e.g., NPCs) and game mechanics (e.g., health). A player’s feeling
of suspense can be adjusted by altering the level of hope, fear, and
uncertainty. Therefore, an SNNG-enhanced game engine could
manage a player’s level of suspense by adding or removing game
objects, diverting NPCs, adjusting game mechanics, and giving
or withholding information. We tested our model by integrating
SNNG into a Pacman game. Our preliminary experiment with
nine subjects was encouraging.
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- Award ID(s):
- 1852516
- NSF-PAR ID:
- 10315350
- Date Published:
- Journal Name:
- Proceedings of the 24th International Conference Information Visualisation
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IV51561.2020.00136
