Narrative gravity is a system-level diagnostic heuristic for explaining why some transmedia storyworlds remain coherent under platform fragmentation while others lose interpretive stability. The problem is not simply how stories circulate or whether a world possesses a stable core. It is what coherence looks like after circulation, when audiences increasingly encounter a world as isolated fragments and sequence cannot reliably do the work of orientation on first contact. This chapter shifts the focus from expansion to what I call the partial-entry problem: the moment coherence must be sustained even when first contact is incomplete. I propose narrative gravity as a heuristic to locate where the work of coherence is actually being carried, whether in texts, paratexts, or community infrastructures. The framework operates across three analytically distinct but systemically linked dimensions: thematic constancy, structural necessity, and ethical resonance. These dimensions work at different analytical scales, narratological, formal, and sociological respectively, but they converge on a shared object: the maintenance infrastructure that keeps a storyworld legible over time. A historical analogue, the Great Siege of Malta, grounds the argument against presentism. The chapter then extends the analysis to feed-based environments and generative AI contexts, introducing Proof of Humanity as a way to track responsibility and trust when provenance becomes unstable.
The method, ECCOLA, is presented, which aims at making the high-level AI ethics principles more practical, making it possible for developers to more easily implement them in practice.
Ville Vakkuri, Kai-Kristian Kemell, P. Abrahamsson· EUROMICRO Conference on Soft...· 64 citations· ⚡6
The goal is to not only refine the accuracy of the LLM-based tool but also to underscore its potential in streamlining the software development lifecycle through proactive code improvement and education.
Z. Rasheed, Malik Abdul Sami, Muhammad Waseem et al.· arXiv.org· 62 citations· ⚡3
A comprehensive overview of how enhanced sampling methods are reshaping the field, with a particular focus on the data-driven construction of collective variables, is provided.
Kai Zhu, Enrico Trizio, Jintu Zhang et al.· Chemical Reviews· 58 citations
The use of large language models to automatically improve the user story quality in Austrian Post Group IT agile teams is explored, with a reference model for an Autonomous LLM-based Agent System developed and implemented at the company.
Zheying Zhang, M. Rayhan, Tomas Herda et al.· International Conference on...· 48 citations· ⚡4
This paper introduces a novel multi-AI-agent system designed to fully automate SLRs, and demonstrates how it substantially reduces the time and effort traditionally required for SLRs while maintaining comprehensiveness and precision.
Abdul Malik Sami, Z. Rasheed, Kai-Kristian Kemell et al.· arXiv.org· 44 citations· ⚡2
The proposed LLM-based multi-agent system automates qualitative data analysis process, creating opportunities for researchers and practitioners, and future improvements focus on enhancing multilingual performance and integrating continuous expert feedback.
Z. Rasheed, Muhammad Waseem, Aakash Ahmad et al.· arXiv.org· 41 citations
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