Modeling lexical attrition in L2 mental lexicon for Chinese EFL learners

Abstract This study aims to model lexical attrition in L2 mental lexicon for Chinese EFL learners using a network science technique. To this end, we constructed a large lexical network with 5746 English words with free association data collected from Chinese EFL college students. The attrition process was modeled by removing connections progressively from the network, leaving words less connected or isolated. Further, we controlled the order in which connections underwent attrition to explore whether order of attrition affected the attrition process. The results showed that: (1) The modeled L2 lexicon was a complex network, whose structure was different from random networks in terms of connectedness, average path lengths, clustering coefficient, power-law degree distribution; (2) Attrition events weakened the structure of L2 mental lexicon by increasingly reducing the number of interconnected words, increasing path lengths between words, and diminishing overall network efficiency, but the process was not linear; (3) The order in which attrition events occur affects the attrition process; specifically, attrition starting from peripheral connections dismantled the lexical network more slowly when compared with random and central-to-peripheral orderings. These findings add to our understanding of the cognitive organization of words in the mind, and provide fresh insight into lexical attrition.