Call for Papers: “Algorithmic Folklore as Transcultural Storytelling” Gathering
Algorithmic folklore “operationalizes the idea that automated systems like recommender systems and machine learning models give rise to new kinds of vernacular creativity - ordinary creative practices emerging outside the scope of professional and cultural recognition”, originating a “repertoire of genres and practices resulting from the [human-machine] encounter” (de Seta, 2024). This fast-growing and rapidly transforming repertoire reflects both the technological developments we’ve been witnessing in the Artificial Intelligence (AI), gaming and social media industries, as well as the distinct human needs and practices that produce and respond to them. Coming to terms with the liminal zones “where agency is traded between human and automated actors” (de Seta, 2024) is a key challenge facing contemporary digital culture scholarship.
To address the need for an in-depth understanding of vernacular culture across platforms and cultures, the electronic book review invites contributions for a forthcoming special Gathering investigating transcultural trends of storytelling within “Algorithmic Folklore”, an emerging phenomenon situated at the intersection of vernacular creative practices and everyday automated systems. The Gathering arises from the shared ambitions of two ongoing research projects: “Algorithmic folklore: The mutual shaping of vernacular creativity and automation (ALGOFOLK)”, led by Gabriele de Seta at the University of Bergen’s Center for Digital Narrative, and “Project StoryMachine: Exploring the implications of recommender based spatial hypertext systems for folklore and the Humanities”, an interdisciplinary collaboration uniting thirteen scholars across six partner institutions in the UK and Germany, co-directed by Claus Atzenbeck (Hochschule Hof), Sam Brooker (London College of Communication), Owen Davies and Ceri Houlbrook (University of Hertfordshire), Sarah Diefenbach (Ludwig-Maximilians Universität München), Astrid Ensslin (Universität Regensburg), Christopher Ohge and Jane Winters (both University of London). Both initiatives examine the cultural practices that are produced by the multi-layered human interactions with automated actors like AI and algorithms, albeit through distinct yet complementary lenses.
By combining ALGOFOLK’s and StoryMachine’s transcultural ethnographic frameworks and narrative-theoretical lenses, this special issue seeks to trace the circulatory co-evolution of vernacular creativity and algorithmic infrastructure across communities, individuals, geographies and platforms. It seeks to generate insights into the complexities and dynamics of algorithmic folklore as a form of posthuman narrative that evolves across platforms, media, communities, languages, and regions and reflects the sociocultural and political biases underlying Large Language Models. In so doing, contributions to this Gathering engage with case studies of AI-generated/assisted folklore and ludofolklore (folklore in and around videogames), with folk theories and lore practices, with emergent myths and metaphors, shapeshifting monsters and other archetypal entities, as well as with transmedial developments of folkloric genres like anecdotes, jokes, memes, rumors, songs, and tales.
The intersection of folklore and automation spans centuries, evolving on a trajectory from mechanical spectacle to computational creativity. In the 17th century, the Magic Lantern transformed oral traditions into visual narratives, shaping public imagination through projected images (Rossell, 2008). Later, Wolfgang von Kempelen’s Mechanical Turk (1770) staged artificial intelligence as theatrical illusion, embedding folklore in mechanical performance (Standage, 2002). With the advent of computational narrative systems, folklore entered a new phase rooted in structuralist theory. Vladimir Propp’s Morphology of the Folktale provided a formal grammar for narrative (Propp, 1968), inspiring systems like ProtoPropp to generate Russian fairy tales algorithmically. James Meehan’s TALE-SPIN introduced character-driven storytelling through problem-solving (Meehan, 1977), while Scott Turner’s MINSTREL adapted plots using analogical reasoning (Turner, 1993). Michael Lebowitz’s UNIVERSE emphasized coherence across narrative threads (Lebowitz, 1984), and Bard, The Automatic Storyteller applied object-oriented programming to model storytelling as modular logic (Peinado & Gervás, 2007). Rather than merely mimicking folklore, these systems encode its structural logic and adaptive dynamism (Thompson, 2019) within computational frameworks, reflecting shifting cultural and technological paradigms.
Parallel to narrative automation, Joseph Weizenbaum’s ELIZA (1966) pioneered chatbot development, simulating empathetic dialogue, and laying the foundation for natural language processing, evolving through the 1990s into rudimentary bots (Berry, 2023). The 2010s brought Generative adversarial networks for speech processing (GANs) for image synthesis, neural Text to Speech (TTS) for speech, and multimodal models (Tan, 2023). The emergence of GPT-3 in 2020, followed by GPT-4 in 2023 and GPT-5 in 2025, marked an inflection point for natural language generation, signaling a transition toward large-scale transformer architectures capable of producing contextually rich, coherent, and stylistically adaptive text. Similarly, in the past five years, text-to-image generators like DALL·E, Midjourney, and Stable Diffusion have significantly advanced image generation, while simultaneous progress in speech, music, and video synthesis have forged new modes of synthetic vernacular content. These models are not only the objects of myths and folk theories in their own right, they also produce artifacts that users integrate into meme cultures, humorous remixes, AI satire, and folk commentary, thereby birthing new forms of cultural expression that integrate a multiplicity of semiotic modes, including material culture, TikTok dance trends and transmedial folklore originating from video game culture.
Algorithmic folklore emerges alongside the platformization and automation of digital culture: as users interact with algorithmic systems that actively shape the production and circulation of content, new forms of transcultural storytelling appear. Early uses of the term “algorithmic folklore” connect it to the folk theories developed by teenagers to make sense of the TikTok algorithm (Akinrinade & Mukogosi, 2019). Folklorists have recognized the growing role of algorithms in the production of narratives (Flinterud, 2023), and media researchers agree on the centrality of vernacular epistemologies in algorithmic culture (Savolainen, 2022; Ruckenstein 2023). As forms of algorithmic media multiply and become ubiquitous across global contexts, algorithmic folklore can be understood as the repertoire of genres and practices resulting from the encounter between vernacular creativity and everyday automation (de Seta, 2024). Manifestations of these (g)local convergences are also multiplying. In mid-2022, artist Steph Maj Swanson shared their finding of a mysterious woman named LOAB, who seemed to “haunt” the outputs of a text-to-image model prompted with a specific negative input. In mid-2023, Reddit users developed a neologism to bait a website publishing AI-generated gaming news into reporting about “glorbo” - a new, non-existing feature of the World of Warcraft videogame. And in early 2025, short video platforms were flooded by AI-generated content depicting “Italian Brainrot” characters, a surrealist blend of animal-object hybrids with faux-Italian names, which users developed into countless versions, lore storylines, and even commercial products. In all these examples, vernacular genres and practices are reconfigured by the growing role that algorithmic systems play in global societies, while also retaining locally inflected humor, affect, and aesthetic logic.
The study of algorithmic folklore benefits from methodological pluralism. Quantitative approaches analyze large datasets to track patterns like meme propagation or frequency of folk narratives; qualitative methods explore interpretive contexts through interviews, discourse analysis, and close readings of vernacular artifacts; computational techniques model circulation dynamics or trace the linguistic characteristics of folklore and its generation; and ethnographic strategies immerse researchers in platforms or communities where algorithmic folklore is produced and shared.
We welcome/are calling for:
- Scholarly essays on algorithmic folklore, digital myth-making, and folklore in virtual networked environments (of 6000-8000 words).
- Short contributions and philosophical provocations on the aesthetics, ethics, politics, economics and/or epistemologies of algorithmic storytelling (max. 3000 words).
- Experimental, multimodal and meta-cognitive creative works including images, remixes, code-poems, and experimental media including scholarly commentary (max. 3000 words). Selected works will be considered for publication in Issue 06 of the digital review.
- Short project reports documenting new collections, tools and/or methodologies or pedagogical innovations (3000-5000 words).
Please send your abstracts to Sabine.Slowik@ur.de and find the Author Guidelines here. For creative works and images, include a brief abstract describing the work, a link to the work itself, and any other supporting materials as one PDF file.
Deadline for abstract submissions: March 31st, 2026
Other important dates:
Notification of acceptance: April 30th, 2026
Full papers due date: June 30th, 2026
Editorial feedback by: October 31st, 2026
Final Version due date: December 18th, 2026
Prospective publication scheduled for February 2027 and beyond.
Guest Editors
Astrid Ensslin
University of Regensburg
Astrid.Ensslin@ur.de
Gabriele de Seta
University of Bergen
Gabriele.Seta@uib.no
Marianne Gunderson
University of Bergen
marianne.gunderson@uib.no
Sabine Slowik
University of Regensburg
Sabine.Slowik@ur.de
About the Projects
The ALGOFOLK project, led by sociologist Gabriele de Seta and funded by the Trond Mohn Foundation (2024–2028), spotlights the concept of algorithmic folklore to explore how everyday users engage with, interpret, and creatively respond to automated digital infrastructures such as generative AI and predictive algorithms.
The StoryMachine project, co-funded by the Deutsche Forschungsgemeinschaft (DFG) and the Arts and Humanities Research Council (AHRC), develops an interactive digital platform to preserve, explore and provide access to folklore. It investigates narrative production in the context of machine learning, focusing on transcultural commonalities and how stories are generated and transformed through algorithmic mediation, while inviting the participation of the broader public.
References
Berry, D. M. (2023). The limits of computation: Joseph Weizenbaum and the ELIZA chatbot. Weizenbaum Journal of the Digital Society, 3(3). https://doi.org/10.34669/WI.WJDS/3.3.2
De Seta, G. (2024). An algorithmic folklore: Vernacular creativity in times of everyday automation. In C. Arkenbout & I. Galip (Eds.), Critical meme reader III: Breaking the Meme, 233–253. Institute of Network Cultures.
Flinterud, G. (2023). ‘Folk’ in the Age of algorithms: Theorizing folklore on social media platforms. Folklore, 134(4), 439–461. https://doi.org/10.1080/0015587X.2023.2233839
Lebowitz, M. (1984). Creating characters in a story-telling universe. Poetics, 13 (3): 171-194.
Meehan, J. R. (1977). TALE-SPIN, An Interactive Program that Writes Stories. In Ijcai, 77: 91-98.
Peinado, F. and Gervás, P. (2007). Automatic Direction of Interactive Storytelling: Formalizing the Game Master Paradigm. In M. Cavazza & S. Donikian (Eds). Virtual Storytelling. Using Virtual Reality Technologies for Storytelling. ICVS 2007. Lecture Notes in Computer Science, 4871, 196-201. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-540-77039-8_18
Propp, V. (1968 [1928]). Morphology of the Folktale: Second Edition. Austin: University of Texas Press. Rossell, D. (2008). Laterna Magica – Magic Lantern 1. Stuttgart: Füsslin.
Ruckenstein, M. (2023). The Feel of Algorithms. University of California Press.
Savolainen, L. (2022). The shadow banning controversy: Perceived governance and algorithmic folklore. Media, Culture & Society, 44(6), 1091–1109. https://doi.org/10.1177/01634437221077174
Standage, T. (2002). The Turk: The Life and Times of the Famous 19th Century Chess-Playing Machine. New York: Walker.
Tan, X. (2023). Neural Text-to-Speech Synthesis. Singapore: Springer Nature.
Thompson, T. (2019). Posthuman Folklore. Jackson: University Press of Mississippi.
Turner, S. R. (1993). MINSTREL: A Computer Model of Creativity and Storytelling. Dissertation, Los Angeles: University of California.