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Recent research has shown that language and the socio-cognitive phenomenaassociated with it can be aptly modeled and visualized through networks oflinguistic entities. However, most of the existing works on linguistic networksfocus only on the local properties of the networks. This study is an attempt toanalyze the structure of languages via a purely structural technique, namelyspectral analysis, which is ideally suited for discovering the globalcorrelations in a network. Application of this technique to PhoNet, theco-occurrence network of consonants, not only reveals several naturallinguistic principles governing the structure of the consonant inventories, butis also able to quantify their relative importance. We believe that thispowerful technique can be successfully applied, in general, to study thestructure of natural languages.

Discovering Global Patterns in Linguistic Networks through Spectral Analysis: A Case Study of the Consonant Inventories