Objective Metrics for Interactive Narrative

Szilas, Nicolas; Ilea, Ioana

doi:10.1007/978-3-319-12337-0_9

Cited by 21 publications

(11 citation statements)

References 15 publications

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“…Future work may include employing Process Mining to study raises in engagement, narrative evaluation, as well as the influence of certain activities in the overall replayability, objective metrics [14], and the emotional dynamics over time using psychophysiological measurements.…”

Section: Discussionmentioning

confidence: 99%

When Did I Lose Them? Using Process Mining to Study User Engagement in Interactive Digital Narratives

Estupiñán

Szilas

2019

Interactive Storytelling

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This work aims at capitalizing advances in the field of Process Mining applied to the domain of Interactive Digital Narratives (IDN), towards the understanding of user engagement, particularly, spotting when and what happened when user engagement dropped. An online IDN system was adapted to implement an engagement sampling protocol, probing 74 users for Continuation Desire during runtime. The playtest dataset was coupled with the engagement self-reports and analyzed using Process Mining. We identified a subset of User-Initiated Actions associated with higher engagement trajectories, as well as actionable feedback for improving the system. We consider Process Mining as an asset for the evaluation of IDN systems and the characterization of the Interactive Narrative Experience.

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Section: Discussionmentioning

confidence: 99%

When Did I Lose Them? Using Process Mining to Study User Engagement in Interactive Digital Narratives

Estupiñán

Szilas

2019

Interactive Storytelling

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“…Visualisation is an important element of mixed creation, for example [40] focuses on low level visualization of interaction design as progression maps. Similarly, [38] discusses automatic structural analysis using graph theory, and [37] suggests some low level computational metrics that show correlation with user experience dimensions. We are interested in higher level insights.…”

Section: Related Workmentioning

confidence: 99%

A Systematic Analysis of User Experience Dimensions for Interactive Digital Narratives

Revi

Millard

Middleton

2020

Lecture Notes in Computer Science

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Providing intelligent feedback to aid authoring has been proposed as a way to speed up authoring, give the author more control, and to enable the authoring of more complex interactive narratives. However, there is little research investigating what concrete feedback items would be useful for interactive digital narrative (IDN) creators. In this paper, we discuss potentially useful feedback items in relation to authoring goals and concerns. We perform a systematic literature review to make a list of concrete feedback items of interest related to the most emphasised concern of authoring -the effect of the interactive narrative on the user. We identify 47 User Experience (UX) dimensions in the IDN literature that could serve as useful feedback items, covering 8 categories -Agency, Cognition, Immersion, Affect, Drama, Rewards, Motivation and Dissonance. This list combines and untangles how different IDN researchers have interpreted and expressed interest in the complex idea of UX in the past decade and gives us insight into what concrete aspects of UX might be useful to estimate via automated feedback.

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“…al. [34] developed such a representation to measure and expand on the "objective metrics" proposed by Szilas and Ilea [44] as part of that project, and here we evaluate and suggest improvements to that representation.…”

Section: Related Workmentioning

confidence: 99%

Evaluation of an automatically-constructed graph-based representation for interactive narrative

Partlan

Carstensdóttir

Kleinman

et al. 2019

Proceedings of the 14th International Conference on the Foundations of Digital Games

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Interactivity and player experience are inextricably entwined with the creation of compelling narratives for interactive digital media. Narrative shapes and buttresses many such experiences, and therefore designers must construct compelling narrative arcs while carefully considering the effects of interaction on both the story and the player. As the narrative becomes more structurally complex, due to choice-based branching and other player actions, designers need to employ commensurately capable models and visualizations to keep track of that growing complexity. However, previous models of interactive narrative have failed to fully capture interactive elements with automated, operationalized visualizations. In this paper, we describe an algorithm for automated construction of a framework-driven, graph-based representation of interactive narrative. This representation more fully and transparently models structural and interactive features of the narrative than did prior approaches. We present an initial evaluation of this representation, based on modified cognitive walkthroughs performed by interactive narrative design and research experts from our research team, and we describe the takeaways for future improvement on interactive narrative modeling and analysis. CCS CONCEPTS • Computing methodologies → Knowledge representation and reasoning; Simulation evaluation; • Applied computing → Computer games; • Software and its engineering → Design languages.

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Objective Metrics for Interactive Narrative

Cited by 21 publications

References 15 publications

When Did I Lose Them? Using Process Mining to Study User Engagement in Interactive Digital Narratives

When Did I Lose Them? Using Process Mining to Study User Engagement in Interactive Digital Narratives

A Systematic Analysis of User Experience Dimensions for Interactive Digital Narratives

Evaluation of an automatically-constructed graph-based representation for interactive narrative

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