Abstract
Past research has demonstrated cross-linguistic, cross-modal, and task-dependent differences in neighborhood density effects, indicating a need to control for neighborhood variables when developing and interpreting research on language processing. The goals of the present paper are two-fold: (1) to introduce CLEARPOND (Cross-Linguistic Easy-Access Resource for Phonological and Orthographic Neighborhood Densities), a centralized database of phonological and orthographic neighborhood information, both within and between languages, for five commonly-studied languages: Dutch, English, French, German, and Spanish; and (2) to show how CLEARPOND can be used to compare general properties of phonological and orthographic neighborhoods across languages. CLEARPOND allows researchers to input a word or list of words and obtain phonological and orthographic neighbors, neighborhood densities, mean neighborhood frequencies, word lengths by number of phonemes and graphemes, and spoken-word frequencies. Neighbors can be defined by substitution, deletion, and/or addition, and the database can be queried separately along each metric or summed across all three. Neighborhood values can be obtained both within and across languages, and outputs can optionally be restricted to neighbors of higher frequency. To enable researchers to more quickly and easily develop stimuli, CLEARPOND can also be searched by features, generating lists of words that meet precise criteria, such as a specific range of neighborhood sizes, lexical frequencies, and/or word lengths. CLEARPOND is freely-available to researchers and the public as a searchable, online database and for download at http://clearpond.northwestern.edu.
Highlights
Phonological and Orthographic Neighborhood Densities In research on language, neighborhoods are a conglomeration of words that are highly similar to one another along a critical characteristic
The database that we present here has been controlled for word frequency to ensure that consistent and comparable tokens are sampled from each language, and provides data regarding word length, neighborhood density, and neighborhood frequency
An ANOVA with language and word length as factors revealed a significant effect of language on total orthographic neighborhood size, F(4,138690) = 12.69, p,0.0001, a significant effect of word length F(12,138690) = 9829.49, p,0.0001, and a significant language x word length interaction F(48,138690) = 222.25, p,0.0001
Summary
Phonological and Orthographic Neighborhood Densities In research on language, neighborhoods are a conglomeration of words that are highly similar to one another along a critical characteristic. Neighbors are defined on the basis of shared linguistic features such as orthography, phonology, or semantics. Because a word’s neighborhood size (i.e., the number of neighbors it has; called neighborhood density) can have an impact on a variety of linguistic tasks and processes, it has become an important psycholinguistic metric. In spite of the focus on neighbors in psycholinguistic research, neighbors are inconsistently identified, across languages. These inconsistencies, which often arise as a result of researchers employing different databases, make it difficult to compare the effects of neighborhood density across studies. The current paper has two goals: (1) to introduce a centralized database of neighborhood information for five commonly-studied languages – Dutch, English, French, German, and Spanish – and provide a single corpus through which neighborhoods can be indexed crosslinguistically; and (2) to compare general properties of neighborhoods across these five languages using this database in order to determine where and how languages differ in respect to their neighborhoods
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