Semantic Spacetime, Semantic Gravity, and the Law of Attention

Abstract

A Framework for Meaning Mass, Contextual Curvature, Attention Allocation, and Evolvable Semantic Systems Description This work develops an integrated theoretical framework for understanding how meaning, attention, and context interact across cognitive, artificial, cultural, and civilizational systems. The framework combines three core concepts: semantic spacetime, semantic gravity, and the law of attention. Semantic spacetime refers to the structured relational environment in which meanings exist, interact, and evolve. Concepts are not treated as isolated units; their significance depends on history, context, relationships, compatibility, direction, and potential. Semantic gravity describes the tendency of high-density or highly connected concepts to attract interpretation, influence nearby meanings, and shape future semantic trajectories. The term is used here as a modeling metaphor rather than a claim of physical gravity. The law of attention addresses how limited cognitive or computational resources are selectively allocated across possible semantic paths. Attention does not merely respond to meaning; repeated attention can also reinforce, reshape, or weaken the semantic structures through which future interpretation occurs. The central dynamic can be summarized as: \text{Semantic Structure}\rightarrow\text{Attention Allocation}\rightarrow\text{Semantic Reinforcement}\rightarrow\text{Reshaped Semantic Structure} This creates a feedback system in which meaning influences attention, attention modifies meaning, and both evolve over time. The framework introduces several candidate constructs, including semantic mass, contextual curvature, attention capture, semantic escape capacity, attention diversity, semantic lock-in, and semantic health. These concepts are used to explore how ideas become central, how interpretive pathways stabilize, how cognitive or cultural systems become trapped in dominant meanings, and how alternative meanings can continue to emerge. A major concern of the work is the balance between continuity and openness. Too little semantic gravity may produce fragmentation and loss of identity. Too much semantic gravity may lead to interpretive lock-in, ideological rigidity, or collapse into a single dominant explanatory structure. The framework therefore proposes that healthy semantic systems require both stable meaning centers and sufficient semantic escape capacity for novelty, criticism, reinterpretation, and reorganization. This principle is especially relevant to artificial intelligence systems. Large language models operate through context-sensitive attention, distributed representations, retrieval processes, and recurrent semantic activation. While the present framework does not equate computational attention with human consciousness, it provides a common conceptual language for studying how semantic structures influence information selection and generation in both human and artificial systems. The work also extends the framework to cultural and civilizational scales. Civilizations can be understood as persistent semantic environments composed of narratives, institutions, values, symbols, archives, languages, and inherited interpretive structures. Certain concepts may accumulate enough semantic mass to influence generations of interpretation, while spaces of ambiguity, pluralism, and conceptual experimentation preserve the ability of civilization to evolve. This leads to a broader formulation: \text{Semantic Health}=\text{Identity Stability}\times\text{Attention Diversity}\times\text{Correctability}\times\text{Semantic Escape Capacity} The study therefore treats meaning not as static content, but as a dynamic field shaped by relationships, attention, memory, repetition, and transformation. Its central proposition is: Attention moves through semantic spacetime; semantic gravity bends the trajectory of attention; repeated attention, in turn, reshapes semantic spacetime. From this perspective, meaning, attention, and context form a continuously evolving system. The purpose of the framework is not to establish a literal physics of meaning, but to provide a structured research language for investigating how semantic environments form, stabilize, attract attention, resist change, and remain capable of further evolution.