Networks in the mental lexicon – contributions from Hungarian

Abstract

Abstract Connections between the units of the mental lexicon store information as complex networks, where nodes represent words. With the emergence of network science characteristics of this mental network can be quantified. Present paper investigates the network structure of the mental lexicon of a non-Indo-European language, Hungarian, using a word association database which collected word association data online. The data is examined with statistical measures of networks: path length and degree centrality are calculated. Comparing the network characteristics of the database to the English South Florida Word Association Database we found that both networks display similar characteristics. We show that the central elements of the two databases are the same words (5 out of 7) and that the most central element in the Hungarian database is money, regardless the used centrality measure. The Hungarian database possesses a single, highly connected core, which defines the network properties of the whole database. This connected core is responsible for the short paths inside the lexicon.