We investigate narrative agency in hu-man–LLM creative co-writing, asking whodrives story development in turn-based collabo-ration. Using a new corpus of human–LLM co-written stories, we apply sentiment and seman-tic modeling to quantify affective alignmentand semantic novelty in turn-taking, and direc-tional measures to assess which agent shapesnarrative progression. Our results show asym-metric influence: human turns introduce greatersemantic novelty and are more likely to shapesubsequent developments, whereas LLM con-tributions predominantly elaborate on human-introduced elements. At the sentiment level,alignment is also asymmetric, but more bidirec-tional: LLMs exhibit stronger turn-level emo-tional adaptation than humans, but both agentstrack each other’s emotional valence and LLMsshow an independent tendency to more pos-itive emotional baselines. These findings in-dicate a complementary division of labor inhuman–LLM co-writing, where humans drivenarrative innovation and direction, while LLMsact as adaptive amplifiers that sustain coherenceand elaborate emerging narratives.