Grasping the invisible: Semantic processing of abstract words

The problem of how abstract word meanings are represented has been a challenging one. In the present study, we extended the semantic richness approach (e.g., Yap, Tan, Pexman, & Hargreaves in Psychonomic Bulletin & Review 18:742–750, 2011) to abstract words, examining the effects of six semantic richness variables on lexical–semantic processing for 207 abstract nouns. The candidate richness dimensions were context availability (CA), sensory experience rating (SER), valence, arousal, semantic neighborhood (SN), and number of associates (NoA). The behavioral tasks were lexical decision (LDT) and semantic categorization (SCT). Our results showed that the semantic richness variables were significantly related to both LDT and SCT latencies, even after lexical and orthographic factors were controlled. The patterns of richness effects varied across tasks, with CA effects in the LDT, and SER and valence effects in the SCT. These results provide new insight into how abstract meanings may be grounded, and are consistent with a dynamic, multidimensional framework for semantic processing.