This work introduces a quantitative methodology, rooted in Complex Systems Science, to map the Cognitive Fingerprint of composers through the analysis of song lyrics. By modeling lyrics as weighted co-occurrence networks, we complement traditional literary analysis by providing a quantitative framework to characterize the architectural and temporal strategies of composition. We employ two main metrics: Structural Entropy (S), which quantifies the logical architecture of word connections (distinguishing between highly organized and random structures), and Temporal Burstiness (B), which measures topical obsession and strategic repetition of central concepts versus linear narrative progression. The intersection of these metrics defines a two-dimensional Phase Space (S×B). Analyzing a corpus of 100 heavy metal bands (over 9,500 lyrics), we demonstrate that this space objectively categorizes authors into distinct cognitive archetypes, such as the Hit Maker (low S, high B) and the Complex Poet (high S, high B). Our findings reveal that stylistic diversity in composition is not due to the breaking of linguistic rules, but rather to the occupation of specific thermodynamic niches within a phase space permitted by human cognition, providing a rigorous basis for neuroscience and stylometry.
Ribeiro et al. (2026) studied this question.