Decoding Word Recognition: How Word Properties and Individual Factors Shape Processing

Reading is one of the most complex abilities that the human mind is capable of, and the process of visual word recognition is the key aspect of it. In order to gain a better understanding of this process, this study investigated the roles of Semantic Neighborhood Density (SND), Orthographic Neighborhood Density (OND), word frequency, word length, and individual differences in reading speed on visual word recognition. Using a lexical decision task and analyzing the data through a linear mixed model, significant effects were found for SND, word frequency, and word length, with a notable interaction between reading speed and word length. Higher SND and word frequency facilitated faster word recognition, while longer word length slowed it down. The interaction revealed that participants with faster reading speeds were less impacted by word length. These findings align with existing computational models of word recognition but also suggest areas for refinement.