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Word associations: network and semantic properties.

Simon De Deyne1, Gert Storms

  • 1Department of Psychologie, University of Leuven, Leuven, Belgium. simon.dedeyne@psy.kuleuven.be

Behavior Research Methods
|April 17, 2008
PubMed
Summary
This summary is machine-generated.

This study reveals that noun responses dominate word associations, forming a network where frequent, early-acquired words are central. These word association networks exhibit small-world properties, with responses often being situation or entity-based.

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Area of Science:

  • Cognitive Psychology
  • Linguistics
  • Network Science

Background:

  • Word associations reveal cognitive processes underlying language.
  • Understanding associative networks aids in modeling semantic memory and concept representation.

Purpose of the Study:

  • To investigate properties of word associations generated in a continuous task.
  • To analyze word class, node centrality, small-world properties, and semantic composition of association networks.
  • To explore the interaction between response position and semantic role in natural concept representation.

Main Methods:

  • Generated word association data through a continuous task.
  • Constructed associative networks and analyzed node centrality.
  • Examined small-world properties and compared them with existing networks.
  • Applied a semantic taxonomy to categorize association responses.

Main Results:

  • Nouns were the most frequent response type, irrespective of cue word class, indicating a paradigmatic response style.
  • Central nodes in the associative network were characterized by high frequency and early acquisition.
  • The generated networks displayed small-world properties, even when denser than discrete task networks.
  • Responses were predominantly thematically related situation and entity responses (e.g., parts, shape, color).

Conclusions:

  • Word association tasks reveal dominant noun-based paradigmatic responses.
  • Associative networks exhibit small-world characteristics with central nodes being frequent and early acquired.
  • Semantic responses are largely situational or entity-based, aligning with theories of natural concept representation.