Proceedings of the Annual Meeting of the Cognitive Science Society

Sensorimotor information plays a fundamental role incognition. However, datasets of ratings of sensorimotorexperience have generally been restricted to several hundredwords, leading to limited linguistic coverage and reducedstatistical power for more complex analyses. Here, we presentmodality-specific and effector-specific norms for 39,954concepts across six sensory modalities (touch, hearing, smell,taste, vision, and interoception) and five action effectors(mouth/throat, hand/arm, foot/leg, head excluding mouth, andtorso), which were gathered from 4,557 participants whocompleted a total of 32,456 surveys using Amazon'sMechanical Turk platform. The dataset therefore representsone of the largest set of semantic norms currently available.We describe the data collection procedures, provide summarydescriptives of the data set, demonstrate the utility of thenorms in predicting lexical decision times and accuracy, aswell as offering new insights and outlining avenues for futureresearch. Our findings will be of interest to researchers inembodied cognition, cognitive semantics, sensorimotorprocessing, and the psychology of language generally. Thescale of this dataset will also facilitate computationalmodelling and big data approaches to the analysis of languageand conceptual representations.