Empirical analysis of scale-free patterns of connectivity in medical term occurrence

Statistical studies in linguistics have shown that relations between word frequencies and their ranks have the regularity of power-law distributions. However, the self-organizing behaviors of word occurrence in the relations have not yet been studied comprehensively. We carried out an empirical analysis of medical term occurrences using the Merck Manual, which is a well-known medical reference book. We investigated medical term connectivity by modeling term occurrences in a text as state transitions in a system. Observing connection frequency distributions, we then found scale-free patterns of connectivity such that frequencies of both incoming and outgoing connections of each term would be power-law distributed. Our results suggest that the term connectivity may give the auto-regulatory dynamic behavior of self-organization. Investigating term connectivity dynamics may significantly advance text processing methodologies.