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Semantic feature production norms for a large set of living and nonliving things

  • Ken McRae
  • , George S. Cree
  • , Mark S. Seidenberg
  • , Chris McNorgan
    • Western University
    • University of Toronto
    • University of Wisconsin-Madison

    Research output: Contribution to journalArticlepeer-review

    868 Scopus citations

    Abstract

    Semantic features have provided insight into numerous behavioral phenomena concerning concepts, categorization, and semantic memory in adults, children, and neuropsychological populations. Numerous theories and models in these areas are based on representations and computations involving semantic features. Consequently, empirically derived semantic feature production norms have played, and continue to play, a highly useful role in these domains. This article describes a set of feature norms collected from approximately 725 participants for 541 living (dog) and nonliving (chair) basic-level concepts, the largest such set of norms developed to date. This article describes the norms and numerous statistics associated with them. Our aim is to make these norms available to facilitate other research, while obviating the need to repeat the labor-intensive methods involved in collecting and analyzing such norms. The full set of norms may be downloaded from www.psychonomic.org/archive.

    Original languageEnglish
    Pages (from-to)547-559
    Number of pages13
    JournalBehavior Research Methods
    Volume37
    Issue number4
    DOIs
    StatePublished - Nov 2005

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