Attraction Formula- A Computational Dynamics Model for Narratology(V3.0)

English This is Version 3.0 of the Attraction Formula theoretical framework, constituting a major paradigm upgrade from the earlier computational narratology model (V1.0, 2026). While V1.0 introduced the Demand-State Network (DCN), dual-track decay (φ-η), and the ρ-trajectory system as domain-specific extensions of general cognitive psychology, V3.0 completes the unification by fully integrating the Four-Domain Emergence and Dual-Track Transduction theory (V29.0) into a rigorous computational dynamics model for narratology. Key theoretical upgrades in V3.0 include:(1) The Unified Attraction Formula E=21⋅m⋅v2⋅s⋅∏C , replacing the previous DCN-ρ architecture with a quantifiable, cross-media kinetic model;(2) Actual vs. Virtual State Motion classification and the First-State Contention mechanism, governing how narratively real versus imagined transitions modulate energy release and attention dominance;(3) Chain-Web Topology, modeling demand-state networks via hierarchical chains, parallel chains, and dynamic bottleneck effects;(4) Two-Stage Selective Focusing, a full attention-mechanism architecture spanning parallel screening, dynamic thresholding, Softmax-based focused execution, cross-chain allocation, and meta-ISS backtracking; and(5) Social-Domain Resonance, explaining collective audience amplification through synchronized substitution. V3.0 thereby transforms narrative attraction analysis from qualitative interpretation to quantitative dynamical-systems computation, with direct applicability to film, literature, interactive media, music, painting, and generative storytelling. License: CC BY-NC-ND 4.0 中文 本文是"吸引力公式"理论框架的第 3.0 版,是从前期计算叙事学模型(V1.0,2026)的重大范式升级。V1.0 将需求态网络(DCN)、双轨衰减(φ-η)与 ρ-轨迹系统作为一般性认知心理学的领域特定扩展引入叙事分析;V3.0 则通过将《四域涌现与双轨转导》理论(V29.0)全面整合进叙事动力学,完成了这一框架的统一化与形式化。 V3.0 的核心理论升级包括:(1)吸引力统一公式 E=21⋅m⋅v2⋅s⋅∏C ,以可量化的跨媒介动力学模型取代早期的 DCN-ρ 架构;(2)实态动与虚态动分类及争首态机制,解释叙事真实态转移与想象态转移如何调制能量释放与注意力主导权;(3)链网拓扑,通过层级链、平行链与动态瓶颈效应建模需求态网络;(4)两阶段选择性聚焦,涵盖并行筛选、动态阈值、Softmax 聚焦执行、跨链分配与元 ISS 回溯的完整注意力机制架构;(5)社会域共振,通过同步代入解释集体观众的吸引力放大效应。 V3.0 由此将叙事吸引力分析从定性解释转变为定量动力学系统计算,可直接应用于电影、文学、交互媒介、音乐、绘画及生成式故事创作。 许可协议: CC BY-NC-ND 4.0