This paper summarizes the results of a large-scale evaluation study of bag-ofwords
distributional models on behavioral data from three semantic priming experiments. The tasks …

This paper presents a large-scale evaluation of bag-of-words distributional models on two
datasets from priming experiments involving syntagmatic and paradigmatic relations. We …

The current study explores a set of variables that have the potential to predict semantic
priming effects for 300 prime–target associates at the item level. Young and older adults …

Many researchers have tried to predict semantic priming effects using a myriad of variables
(eg, prime–target associative strength or co-occurrence frequency). The idea is that …

In recent decades, many computational techniques have been developed to analyse the
contextual usage of words in large language corpora. The present study examined whether …

Semantic priming has been a focus of research in the cognitive sciences for more than thirty
years and is commonly used as a tool for investigating other aspects of perception and …

In two experiments, we attempted to replicate and extend findings by Günther et al. that word
similarity measures obtained from distributional semantics models—Latent Semantic …

The current study examines the underlying processes of semantic priming using the largest
priming database available (ie, Semantic Priming Project, Hutchison et al. Behavior …

In distributional semantics models (DSMs) such as latent semantic analysis (LSA), words are
represented as vectors in a high-dimensional vector space. This allows for computing word …

The theoretical “difficulty in separating association strength from [semantic] feature overlap”
has resulted in inconsistent findings of either the presence or absence of “pure” associative …