Quantifying social semantics: An inclusive definition of socialness and ratings for 8388 English words

Behav Res Methods. 2023 Feb;55(2):461-473. doi: 10.3758/s13428-022-01810-x. Epub 2022 Mar 14.

Abstract

It has been proposed that social experience plays an important role in the grounding of concepts, and socialness has been proffered as a fundamental organisational principle underpinning semantic representation in the human brain. However, the empirical support for these hypotheses is limited by inconsistencies in the way socialness has been defined and measured. To further advance theory, the field must establish a clearer working definition, and research efforts could be facilitated by the availability of an extensive set of socialness ratings for individual concepts. Therefore, in the current work, we employed a novel and inclusive definition to test the extent to which socialness is reliably perceived as a broad construct, and we report socialness norms for over 8000 English words, including nouns, verbs, and adjectives. Our inclusive socialness measure shows good reliability and validity, and our analyses suggest that the socialness ratings capture aspects of word meaning which are distinct to those measured by other pertinent semantic constructs, including concreteness and emotional valence. Finally, in a series of regression analyses, we show for the first time that the socialness of a word's meaning explains unique variance in participant performance on lexical tasks. Our dataset of socialness norms has considerable item overlap with those used in both other lexical/semantic norms and in available behavioural mega-studies. They can help target testable predictions about brain and behaviour derived from multiple representation theories and neurobiological accounts of social semantics.

Keywords: Grounded cognition; Lexical decisions; Semantic cognition; Social cognition; Word ratings.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain
  • Emotions
  • Humans
  • Language*
  • Reproducibility of Results
  • Semantics*