There is a lot being written about the stylistic tells of AI writing (em-dashes, etc.) but this paper looks at AI narrative tells

Fascinating differences between AI & human narrative, and asking AI to write in different styles doesn’t do much to change it https://t.co/azkRHz34NQ https://t.co/oTxSGBNYYE

StoryScope: Investigating idiosyncrasies in AI fiction

Source: https://arxiv.org/abs/2604.03136 View PDF

Abstract:As AI-generated fiction becomes increasingly prevalent, questions of authorship and originality are becoming central to how written work is evaluated. While most existing work in this space focuses on identifying surface-level signatures of AI writing, we ask instead whether AI-generated stories can be distinguished from human ones without relying on stylistic signals, focusing on discourse-level narrative choices such as character agency and chronological discontinuity. We propose StoryScope, a pipeline that automatically induces a fine-grained, interpretable feature space of discourse-level narrative features across 10 dimensions. We apply StoryScope to a parallel corpus of 10,272 writing prompts, each written by a human author and five LLMs, yielding 61,608 stories, each ~5,000 words, and 304 extracted features per story. Narrative features alone achieve 93.2% macro-F1 for human vs. AI detection and 68.4% macro-F1 for six-way authorship attribution, retaining over 97% of the performance of models that include stylistic cues. A compact set of 30 core narrative features captures much of this signal: AI stories over-explain themes and favor tidy, single-track plots while human stories frame protagonist’ choices as more morally ambiguous and have increased temporal complexity. Per-model fingerprint features enable six-way attribution: for example, Claude produces notably flat event escalation, GPT over-indexes on dream sequences, and Gemini defaults to external character description. We find that AI-generated stories cluster in a shared region of narrative space, while human-authored stories exhibit greater diversity. More broadly, these results suggest that differences in underlying narrative construction, not just writing style, can be used to separate human-written original works from AI-generated fiction.

Submission history

From: Jenna Russell [view email] **[v1]**Fri, 3 Apr 2026 15:56:38 UTC (2,053 KB) **[v2]**Mon, 6 Apr 2026 01:44:49 UTC (2,052 KB) **[v3]**Wed, 8 Apr 2026 13:25:18 UTC (2,052 KB) **[v4]**Mon, 13 Apr 2026 20:04:18 UTC (2,045 KB)