Author ORCID Identifier

Author ORCID Identifier

Cristo Leon

Name: Cristo Leon, PhD in Organizational Leadership
Position: Director of Research, Jordan Hu College of Science & Liberal Arts, Office of Research & Development
Institution: New Jersey Institute of Technology
Address: 323 Martin Luther King Jr. Blvd., Newark, NJ 07102-1982, USA
Email: [email protected]
ORCID: https://orcid.org/0000-0002-0930-0179
Role: First author and corresponding author

Julian Marcone

Name: Julian Marcone
Position: CEO
Institution: Kali Foundation
Address: 11415 Tallinn, Estonia
Email: [email protected]
ORCID: https://orcid.org/0009-0009-6896-7051

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Document Type

Article

Description

This article presents a scoping review of 35 studies examining multimedia data in tabletop role-playing game (TTRPG) research and proposes a Polyvocal Semantic Infrastructure (PSI) for organizing, connecting, retrieving, and reusing multimodal evidence. The framework emphasizes provenance, interpretive plurality, and future AI-assisted analysis while preserving the contextual richness of TTRPG scholarship.

Publication/Submission Date

9-14-2026

Keywords

Tabletop role-playing game (TTRPG) research increasingly produces complex multimodal and multimedia evidence, including speech, audiovisual recordings, character sheets, maps, platform traces, session notes, game-state data, and retrospective documentation. However, the field lacks a stable methodological infrastructure for organizing, comparing, retrieving, and reusing these heterogeneous forms of play-derived evidence. This article presents a scoping review of computational, multimodal, multimedia, and knowledge-organization approaches used to analyze TTRPG-derived data. The review followed PRISMA-informed transparency practices, used SPIDER to define the review scope, and synthesized 35 included sources through an extraction matrix, a research-question alignment matrix, and keyword co-occurrence analysis. The findings show that TTRPG research is distributed across publication ecosystems, data types, analytical purposes, and levels of formalization. Existing studies use qualitative interpretation, discourse and conversation analysis, player-experience evaluation, structured datasets, natural language processing, named entity recognition, semantic annotation, AI-assisted generation, and controlled vocabularies. However, these approaches remain weakly coordinated across disciplinary vocabularies, data models, and formalization practices. To address this gap, the article proposes a Polyvocal Semantic Infrastructure that responds to a double ontological problem in TTRPG research: the same object is named in multiple ways, and the same term is used for different objects across communities, systems, and disciplines. Operationalized through a semantic atlas and scope ladder, this infrastructure preserves interpretive plurality while supporting comparison, retrieval, provenance tracking, and future AI-assisted analysis of TTRPG-derived Multimedia Play Data.

Disciplines

Arts and Humanities

Comments

Acknowledgments: The authors would like to acknowledge the review, discussions, and conversa-tions with Rodrigo Santamaría, Marcos O. Cabobianco, and Tamara Pandolfi, whose feedback and interdisciplinary perspectives contributed to the conceptual development of this work. The authors also acknowledge the librarians at the Robert W. Van Houten Library at the New Jersey Institute of Technology for their support in literature access, retrieval, and research consultation. During the preparation of this manuscript, the authors used ChatGPT (version 5.5 Thinking) for language refinement, structural drafting, and conceptual organization. The authors reviewed and edited the output and take full responsibility for the content of this publication.

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Toward a Polyvocal Semantic Infrastructure for Tabletop Role-Playing Game Research: A Scoping Review of Multimedia Play Data

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