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Call for papers

The deadline for submissions is 30 September 2025.

Themed issue description

In recent years, the technological and theoretical tools necessary to bridge data-driven methods and narrative studies have developed rapidly, offering new perspectives about the way we structure, interpret, and generate stories across diverse media and cultural contexts. This special issue aims to bring together interdisciplinary research to advance our understanding of narratives through computational methods — from theoretical explorations to empirical studies and creative applications.

Narratives lie at the heart of human experience, shaping communication, cognition, and culture. Computational Narratology is at the crossroads of narratology, digital humanities, computer science, and artificial intelligence, as it employs computational tools to analyze, generate, and model narrative structures and elements. By integrating data-driven methods (e.g., machine learning, natural language processing, and knowledge representation) with long-standing narratological theories, Computational Narratology opens up new possibilities for:

• Understanding and interpreting narratives in traditional textual forms and multimodal or interactive media (games, virtual environments, films, and more).  
• Creating new story-generation frameworks for narrative creativity.  
• Broadening the scope of cultural and cross-lingual narrative studies, offering empirical insights into global storytelling practices.  
• Developing real-world applications in education, entertainment, marketing, social science research, and beyond.

We particularly encourage contributions that represent methodological approaches and novel computational techniques. Submissions may address textual, multimodal, or interactive narratives and can explore various languages and cultural contexts.

Topics of interest 

We invite submissions on (but not limited to) the following topics:

1. Narrative Structure, Representation and Analysis

• Computational modeling of plots, character networks, thematic progression, and focalization  
• Algorithms for segmenting and annotating narratives, detecting events, and analyzing temporal order  
• Formal models of plot progression, “story grammars”, and application of narrative schemas  

2. Narrative Generation and Evaluation  

• Automated story generation using language models, symbolic AI, hybrid approaches, or procedural methods  
• Evaluation methods for generated narratives and their aesthetic or experiential impact  

3. Sentiment, Emotion, and Affect  

• Sentiment analysis and character relationship modeling within narratives  
• Extraction and evaluation of emotional arcs for narrative modelling
• Modeling of human engagement and immersion in stories  
• Cognitive and psychological dimensions of narrative consumption and interpretation  

4. Cross-Cultural and Multilingual Narratology  

• Comparative computational studies of narrative forms across languages and cultures  
• Machine translation and its implications for cross-lingual narrative analysis  
• Universal vs. culturally-specific narrative structures  

5. Narratives in Non-Traditional and Multimodal Media 

• Computational analysis of comics, films, games, interactive and branching narratives  
• Approaches to studying user-driven, non-linear, and emergent storytelling  
• Multimodal tools and frameworks that integrate text, audio, and visual data

6. Corpus Development and Annotation  

• Creation of annotated corpora for narratological research (plot, characters, setting, rhetorical devices, etc.)  
• Automated and semi-automated annotation tools and frameworks  
• Best practices and standards for large-scale narrative data  

7. Theoretical and Methodological Advances  

• Integration of classic narratological theories with AI-driven techniques  
• Ethical considerations in large scale story generation and narrative manipulation  
• Explorations of narrative ethics, bias, and representational justice  

8. Applications of Computational Narratology  

• Educational tools to enhance learning experiences through story-driven approaches  
• Real-world applications in journalism, marketing, public policy, and cultural analytics  
• Human–computer interaction and design for narrative systems.

Submission process 

All submissions should be made via the CHR online peer review system (ScholarOne). Authors should consult the journal’s Authors instructions prior to submission.

Contacts 

If you have questions about this themed issue, please reach out to the Guest Editors:

• Yuri Bizzoni (Center for Humanities Computing, Aarhus University, Denmark): yuri.bizzoni@cas.au.dk
• Federico Boschetti (CoPhiLab, Cnr-Istituto di Linguistica Computazionale “Antonio Zampolli”, Italy): federico.boschetti@ilc.cnr.it
• Katja Tereshko (Huygens Institute, The Netherlands): katja.learndutch@gmail.com

For any questions related to editorial policy or the submission process, please contact the journal’s Editorial Office at chr@cambridge.org.