At the HUMAN’25 workshop, four members of the hypertext research community reflected on the “hypertext as method” argument; specifically, the idea that hypertext should be understood as a method of inquiry rather than as merely a type of system. These community members presented position statements to address challenges stemming from this proposed method, including designing interfaces for LLMs, supporting annotation and note-taking as cognitive tools, evaluating AI as a collaborator in intellectual work, and applying hypertext analysis to historical information networks. These positions and the subsequent discussion contained several common themes, including a preference for augmentation over automation and concerns that generative AI may encourage users to disengage from critical thinking.

This paper introduces StoryMachine (AHRC grant ref. AH/Z507222/1, DFG project number 547532269), a newly funded transdisciplinary project (2025-2028) conducted jointly by six research groups in Germany and the UK, which aims to develop an innovative digital infrastructure to preserve, explore, and democratize access to folklore traditions and vernacular storytelling practices around the world, with a particular focus on German- and English-speaking communities. Recognizing folklore as a cornerstone of shared cultural identity, the project addresses critical challenges in archival practices, and in particular the lack of interactive, dynamic, accessible and inclusive tools for exploring both traditional and emerging folk narratives. Existing approaches to digital folklore archiving remain largely static, focusing on isolated collections without fostering meaningful exploration, collaboration, or analysis. StoryMachine redefines these paradigms by integrating spatial hypertext and recommender systems to create a visually dynamic, user-centered interface.

The transdisciplinary Digital Humanities project StoryMachine, conducted jointly (2025–2028) by six research groups in Germany and the UK, is developing an innovative digital infrastructure to preserve, explore, and democratize access to folklore traditions and vernacular storytelling practices around the world, with emphasis on German- and English-speaking communities. Recognizing folklore as a cornerstone of shared cultural identity, the project addresses critical challenges in archival practices, and particularly the lack of interactive, dynamic, accessible and inclusive tools for exploring both traditional and emerging folk narratives. Existing approaches to digital folklore archiving remain largely static, focusing on isolated collections without fostering meaningful exploration, collaboration, or analysis. StoryMachine redefines these paradigms by integrating spatial hypertext and recommender systems to create a visually dynamic, user-centered interface, which empowers users to actively participate in ongoing transregional, transcultural narrative practices while expanding previously dominant linear forms of storytelling to reflect the diversity and multifaceted nature of contemporary folklore.

Recently, a call was made for the hypertext community to “return to its roots” by re-exploring our interdisciplinary nature, renewing the areas of common interest with the diverse set of researchers that comprise this community. In this paper, we lay out a set of research questions inspired by several research threads that were active in prior iterations of the hypertext community, but have recently slipped from our focus. The developments of the intervening years have in many cases added nuance and depth to these open questions, potentially making them of renewed interest to the present community. We present these questions through the lens of a maximalist vision that places structure front and center of our model of the world, relegating data to second-class status. We follow the implications of this vision to recover a set of open questions that once occupied, and may once again occupy, a large portion of the interest of the hypertext community.

Traditional spatial hypertext systems, predominantly limited to two-dimensional (2D) interfaces, offer limited support for addressing long debated inherent problems such as orientation difficulties and navigation in large information spaces. In this context, we present opportunities from interdisciplinary fields such as immersive analytics (IA) and embodied cognition that may mitigate some of these challenges. However, while some research has explored the extension of spatial hypertext to three dimensions, there is a lack of discussion on recent advances in virtual reality technologies and related fields, and their potential impact on immersive spatial hypertext systems. This paper addresses this gap by exploring the integration of immersive technologies into spatial hypertext systems, proposing a novel approach to enhance user engagement and comprehension through three-dimensional (3D) environments and multisensory interaction.

This paper explores the integration of hypertext structures within Virtual Reality (VR) environments, differentiating between two distinct design philosophies: VR as a native framework for 3D embodiment-enabled spaces similar to traditional 2D spatial hypertext, and utilizing hypertext to enhance VR experiences. Focusing on the latter approach, we propose an abstract knowledge layer that bridges typical VR systems and human thinking, thus facilitating the integration of human cognitive capabilities. Finally, we explore ethical implications of VR systems that arise in the presented context and propose hypertext as a paradigm to address some of these concerns.

The paper presents SPORE, a spatial hypertext-oriented recommender system. Integrating spatial hypertext and recommender systems with a structuralist approach to narrative, SPORE seeks to mimic the process of storybreaking that already exists in the creative industries. This more organic, exploratory approach offers a potential “third way” for co-creation with artificial intelligence.

This paper posits that spatially structured concepts can function as a visual representation of knowledge, a notion supported by common methods of eliciting and presenting mental models. Despite an existing gap in understanding the correlation between visual structure and knowledge representation, this study aims to clarify this relationship. To this end, we conducted a study wherein participants rated pairwise relationships between ten concepts on a discrete scale ranging from one to ten. Subsequently, we compared these ratings with weights derived from the distances between concepts in human-generated spatial structures. Our findings unveil a linear relationship between the weights obtained through both methods, indicating that spatial arrangements may systematically reflect and encode knowledge.

This paper considers hypertext in its various forms as a paradigm that has the potential to reduce a number of ethical concerns that come with (generative) AI. Based on a user scenario, the paper points out some ethical issues and explains how they can be addressed by hypertext. To do so, it distinguishes between System 1 (fast automation of simple tasks) and System 2 (critical thinking) tasks. Drawing on existing publications in philosophy, the paper argues that AI systems cannot be moral agents; they cannot be trustworthy or truly intelligent. This breaks with some of the wording, partly used for marketing purposes, that currently makes “artificial intelligence” a hype. The analysis follows the three most important ethical theories: deontology, consequentialism, and virtue ethics. The paper concludes that hypertext, although a niche topic, is already prepared to solve some of the most prominent and urgent ethical issues in AI.

As collaborative technologies become integral in both professional and leisurely settings, especially during the rise of remote work and digital communities due to COVID-19, understanding the user experience (UX) factors is critical. This study aims to explore the differential importance of these UX factors across professional and leisure contexts, leveraging the widespread use of collaboration tools for an in-depth analysis. The objective of the study is to identify and assess key UX factors in collaboration tools, and to quantify their differential impact in professional and leisure settings. Our research underscores the nuanced role of context in evaluating User Experience (UX) factors’ importance in collaboration tools, with significant variances observed across professional and leisure settings. While some UX factors, including accessibility, clarity, and intuitive use, maintained universal importance across contexts and tools, others—specifically dependability and efficiency—contradicted assumptions of being universal "hygiene factors", demonstrating the complexity of UX evaluations. This complexity necessitates a differentiated approach for each context and collaboration tool type, challenging the possibility of a singular evaluation or statement.

SPORENLP is a recommendation system designed to review scientific literature. It operates on a sub-dataset comprising 15,359 publications, with a total of 117,941,761 pairwise comparisons. This dataset includes both metadata comparisons and text-based similarity aspects obtained using natural language processing (NLP) techniques.Unlike other recommendation systems, SPORENLP does not rely on specific aspect features. Instead, it identifies the top k candidates based on shared keywords and embedding-related similarities between publications, enabling content-based, intuitive, and adjustable recommendations without excluding possible candidates through classification. To provide users with an intuitive interface for interacting with the dataset, we developed a web-based front-end that takes advantage of the principles of spatial hypertext. A qualitative expert evaluation was conducted on the dataset. The dataset creation pipeline and the source code for SPORENLP will be made freely available to the research community, allowing further exploration and improvement of the system.

In personalized interaction between humans and computers, not only computers and personalization algorithms learn about the users: the users also learn about the system’s behavior and adapt their expectations accordingly. Particularly, as users expect systems to support their daily activities, this feedback loop may result in long-term changes in these daily activities and user decisions themselves. This can be observed in activities as different as autonomous driving and social media consumption. In this chapter, we investigate these effects by reviewing and analyzing a wide range of relevant literature.

We are entering a period of unprecedented collaboration between authors and computers, where artificial intelligence in particular seems likely to act increasingly in a co-authoring capacity. Automated or procedural storytelling represents one exciting avenue of research. By entering prompts and parameters into an AI text generator like ChatGPT, authors could leverage an enormous textual corpus to generate a “new” work that appears to have been authored by a human.

This paper proposes an alternative platform, one more reflective of the collaborative and organic creative process. Approached as a tool for augmentation, Mother showcases the potential for spatial hypertext to work alongside the author.

Two years ago the idea of International Teaching and Research in Hypertext (INTR/HT) was introduced. This paper follows up on this idea and further develops new thoughts on this topic, based on the experiences gained from three university courses taught under the umbrella of INTR/HT. We conclude we have envisioned a model for the future of international and interdisciplinary education in hypertext that has the potential to raise the next generation of hypertext researchers through efforts of collaborative teaching and learning activities.

The paper presents SPORE, a Spatial Recommender System. As we enter a period of unprecedented collaboration between authors and computers, where artificial intelligence in particular seems likely to act increasingly in a co-authoring capacity, SPORE offers a different approach to collaboration. More organic and exploratory than other automated or procedural systems, SPORE aims to mimic the process of storybreaking that already exists in the creative industries.

Vladimir Propp (1895–1970) was a Russian folklorist, who identified what he considered the 31 fundamental actions of major characters and their consequences for a story, actions which he called functions. This paper focuses on one specific part of this principle—spheres of action—and considers how they might be explored using SPORE and its underlying infrastructure Mother, a spatial hypertext-based recommender system developed by the authors.

Recommender Systems are omnipresent in our digital life. Most notably, various media platforms guide us in selecting videos, but recommender systems are also used for more serious goals, such as news selection, political orientation and work decisions. As argued in this survey and position article, the paradigm of recommendation-based feeds has changed user behaviour from active decision making to rather passively following recommendations and accepting possibly suboptimal choices that are deemed “good enough”. We provide a historic overview of media selection, discuss assumptions and goals of recommender systems and identify their shortcomings, based on existing literature. Then, the perspective changes to hypertext as a paradigm for structuring information and active decision making. To illustrate the relevance and importance of active decision making, we present a use case in the field of TV or media selection and (as a proof of concept) carried over to another application domain: maintenance in industry. In the discussion section, we focus on categorising these actions on a spectrum of “system-1” (fast and automated) tasks and “system-2” (critical thinking) tasks. Further, we argue how users can profit from tools that combine active (spatial) structuring and categorising with automatic recommendations, for professional tasks as well as private, leisure activities.