Journal Information
ACM Transactions on Intelligent Systems and Technology (TIST)
https://dl.acm.org/journal/tist
Impact Factor:
6.6
Publisher:
ACM
ISSN:
2157-6904
Viewed:
23046
Tracked:
24
Call For Papers
ACM Transactions on Intelligent Systems and Technology is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective. An intelligent system is one that uses artificial intelligence (AI) techniques to offer important services (e.g., as a component of a larger system) to allow integrated systems to perceive, reason, learn, and act intelligently in the real world.
Last updated by Dou Sun in 2025-09-26
Special Issues
Special Issue on New Frontiers in Interactive Storytelling and Computational Models of Narrative
Submission Date: 2025-12-01

Guest Editors: • Belén Dìaz Agudo, Universidad Complutense de Madrid (Spain), belend@ucm.es • Pasquale Lisena, EURECOM (France), pasquale.lisena@eurecom.fr • Paul Mulholland, The Open University (UK), paul.mulholland@open.ac.uk • Maria Angela Pellegrino, Università degli Studi di Salerno (Italy), mapellegrino@unisa.it This special issue aims to investigate the integration of knowledge-driven methods with state-of-the-art AI techniques, particularly (large) language models (LLMs) and Generative AI (GenAI), in the context of digital creativity and computational storytelling. With the increasing ability of LLMs to generate complex narrative structures, there is growing interest in how these technologies can be combined with symbolic, explainable approaches—such as knowledge graphs (KGs)—to support richer, more adaptive, and context-aware narrative systems. The issue targets a wide range of creative and interactive domains, including cultural heritage, video games, education, cognitive technologies, and social robotics. These applications require narrative as a central structuring element to communicate, influence, and organize human experience. By inviting contributions from fields such as Natural Language Processing, Knowledge Representation, Semantic Web, and Human-Computer Interaction, the special issue fosters an interdisciplinary approach to understanding and advancing computational models of narrative. Ultimately, this issue seeks to bridge the gap between technical innovation and creative practice, promoting novel methods that overcome current limitations of LLMs—such as hallucinations and lack of explainability—while enhancing storytelling potential. It encourages research that pushes the boundaries of how stories are constructed, interpreted, and experienced in digital and interactive environments, setting the stage for new applications and theoretical advancements in narrative-centered AI systems. Topics We invite submissions of original research articles, case studies, review articles, and position papers that address the following topics (but not limited to): • Design and implementation of ontologies and/or knowledge graphs for supporting storytelling, ranging from modeling emotions, event-centric and/or temporal-aware representation of stories, human, moral and cultural values, to linguistic or commonsense aspects. • Design and implementation of Culturally and Socially-Aware specialized Language Models (not necessarily large) able to limit the hallucination problems of LLMs and to remain compliant to hard constraints for the generation of stories. • System design and interfaces focusing on solutions to author interactive storytelling supported by Semantic Web technologies. • Approaches, infrastructures, interaction design and/or toolkits that enable digital creativity via Semantic Web technologies or computational narrative analysis and generation using knowledge graphs • Design and implementation of creative applications of computational narratives in digital media, games, or immersive environments • Studies, prototypes, or investigations that explore the social impact of automated storytelling technologies, ranging from ethical issues, information disorder, to explicability. • Domain-specific and practical applications of knowledge graphs and storytelling in various fields, ranging from education, gaming, digital humanities to social robotics. • Task-oriented applications of KGs (also integrated with other Artificial Intelligence techniques, such as LLM or others) for the automatic generation of narratives such as videogame landscapes, explainable and interpretable log file analysis, narrative interaction planning in human-robot interaction, automatic generation of stories, natural language generation for explicability of RDF triples via (data-driven) stories • Empirical investigation or user studies evaluating interactive stories and narrative systems. Findings, guidelines, and/or studies related to success stories or reporting negative results related to the application of knowledge graphs to author stories. • Critical literature reviews with clear relevance to point out and/or compare study, design, or use of knowledge graphs, combined eventually with LLM or other AI-driven approaches, in the context of digital creativity. Important Dates • Submissions deadline: December 1, 2025 • First-round review decisions: March 1, 2026 • Deadline for revision submissions: June 1, 2026 • Notification of final decisions: September 1, 2026 • Tentative publication: October 15, 2026 Submission Information Submissions must be prepared according to the TIST submission guidelines (https://dl.acm.org/journal/tist/authorguidelines) and must be submitted via Manuscript Central (https://mc.manuscriptcentral.com/tist). The submitted papers must be written in English and describe original research that has not been published nor is currently under review by other journals or conferences. An extended version of a published conference paper can be submitted to TIST for consideration if (1) the conference paper does not already appear in a journal and (2) it contains significant new material (25% according to ACM Policy). The review process will proceed on a rolling basis. For questions and further information, please contact Maria Angela Pellegrino (mapellegrino@unisa.it).
Last updated by Dou Sun in 2025-09-26
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