The orthographic similarity structure of English words: Insights from network science

Abstract Network science has been applied to study the structure of the mental lexicon, the part of long-term memory where all the words a person knows are stored. Here the tools of network science are used to study the organization of orthographic word-forms in the mental lexicon and how that might influence visual word recognition. An orthographic similarity network of the English language was constructed such that each node represented an English word, and undirected, unweighted edges were placed between words that differed by an edit distance of 1, a commonly used operationalization of orthographic similarity in psycholinguistics. The largest connected component of the orthographic language network had a small-world structure and a long-tailed degree distribution. Additional analyses were conducted using behavioral data obtained from a psycholinguistic database to determine if network science measures obtained from the orthographic language network could be used to predict how quickly and accurately people process written words. The present findings show that the structure of the mental lexicon influences lexical access in visual word recognition