Event Indexed Memory Maps Audit Character Consistency and Plot Continuity in Serial Fiction Narrative Arcs
Keywords:
Consistency Auditing, Serial Fiction, Event-Indexed Memory Maps, Narrative InformaticsAbstract
The rapid proliferation of serialized fiction across digital platforms has introduced unprecedented challenges in maintaining narrative consistency over extended publication periods. Authors of serial fiction often produce millions of words over several years, leading to an inevitable degradation in the precise recall of established story facts, character states, and temporal timelines. This paper introduces the concept of Event-Indexed Memory Maps as a novel computational framework designed specifically for consistency auditing in long-form serial narratives. By structuring narrative data chronologically and linking discrete story events to specific entity states, this framework provides a dynamic, queryable database that mirrors the evolving reality of the fictional world. Our research investigates the theoretical foundations of memory indexing in computational narratology and proposes a comprehensive methodology for automating the extraction and auditing of these narrative elements. Through rigorous analysis of a corpus comprising heavily serialized texts, we demonstrate that Event-Indexed Memory Maps significantly outperform traditional keyword-based tracking and manual story bibles in detecting continuity errors. The results indicate a substantial reduction in false positives when auditing complex state transitions, such as spatial locations, character affiliations, and inventory possession. This paper concludes by discussing the broader implications of narrative informatics for the future of digital authorship, highlighting how computational tools can alleviate the cognitive burden on creators while preserving the structural integrity of expansive fictional universes.
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Copyright (c) 2026 Marco Fontana, Violet Palmer
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