Proceedings of the Annual Meeting of the Cognitive Science Society

Words frequently acquire new senses, but the mental processthat underlies the historical emergence of these senses is oftenopaque. Many have suggested that word meanings develop innon-arbitrary ways, but no attempt has been made to formalizethese proposals and test them against historical data at scale.We propose that word meaning extension should reflect a drivetowards cognitive economy. We test this proposal by exploringa family of computational models that predict the evolution ofword senses, evaluated against a large digitized lexicon thatdates back 1000 years in English language history. Our find-ings suggest that word meanings not only extend in predictableways, but also that they do so following an historical path thattends to minimize cognitive cost - through a process of nearest-neighbor chaining. Our work contributes a formal approach toreverse-engineering mental algorithms of the human lexicon.