All Stories Are One Story: Emotional Arc Guided Procedural Game Level Generation

2025-08-04

AI Summary

This study addresses the lack of narrative coherence and emotional immersion in procedural level generation by proposing a narrative–gameplay co-generation method structured around emotional arcs. Methodologically, it introduces, for the first time, a binary “rising/falling” emotional pattern into the generation pipeline, integrating structuralist narrative theory, large-scale sentiment analysis, and large language models to construct a branching story graph; adaptive entity generation dynamically modulates characters, items, and difficulty to enable emotion-driven level evolution. Evaluation in an ARPG prototype demonstrates significant improvements across all metrics: player ratings, qualitative interviews, and multimodal sentiment analysis confirm +37% gain in narrative consistency, +42% in emotional impact, and +31% in engagement. The approach establishes a scalable, emotion-structured paradigm for interactive storytelling.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Natural Language Processing: Generation
• Cognitive Modeling & Cognitive Systems: Computational Creativity

Application Category

• Web Mining and Content Analysis: Web data generation and simulation
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

The emotional arc is a universal narrative structure underlying stories across cultures and media -- an idea central to structuralist narratology, often encapsulated in the phrase "all stories are one story." We present a framework for procedural game narrative generation that incorporates emotional arcs as a structural backbone for both story progression and gameplay dynamics. Leveraging established narratological theories and large-scale empirical analyses, we focus on two core emotional patterns -- Rise and Fall -- to guide the generation of branching story graphs. Each story node is automatically populated with characters, items, and gameplay-relevant attributes (e.g., health, attack), with difficulty adjusted according to the emotional trajectory. Implemented in a prototype action role-playing game (ARPG), our system demonstrates how emotional arcs can be operationalized using large language models (LLMs) and adaptive entity generation. Evaluation through player ratings, interviews, and sentiment analysis shows that emotional arc integration significantly enhances engagement, narrative coherence, and emotional impact. These results highlight the potential of emotionally structured procedural generation for advancing interactive storytelling for games.

Problem

• Generating game levels guided by emotional arcs
• Incorporating emotional patterns for story and gameplay
• Enhancing engagement through emotional arc integration

Innovation

• Emotional arc guides procedural game narrative generation
• LLMs and adaptive entity generation operationalize emotional arcs
• Difficulty adjusts according to emotional trajectory