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Core features: measures and characterization for different languages.

Leticia Vivas1, Maria Montefinese2,3, Marianna Bolognesi4

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Summary
This summary is machine-generated.

Semantic feature norms reveal stable concept representations across Italian, Spanish, and English. While core features are consistent, cross-linguistic variations offer insights into multilingual understanding.

Keywords:
Conceptual representationFeature listing taskSemantic features

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Area of Science:

  • Cognitive Psychology
  • Linguistics
  • Psycholinguistics

Background:

  • The feature-based view posits concepts as networks of weighted semantic features.
  • Semantic feature norms quantify feature informativeness and distinctiveness.
  • Cross-linguistic comparisons of these norms are scarce.

Purpose of the Study:

  • To investigate cross-linguistic similarities and differences in semantic representations.
  • To analyze aggregated core features of concrete concepts across languages.
  • To compare semantic features between natural and artefact domains.

Main Methods:

  • Identified salient features for concrete concepts.
  • Classified features by type.
  • Conducted comparative analyses across Italian, Spanish, and English.
  • Provided descriptive statistics for feature data.

Main Results:

  • Concept characterization shows considerable cross-linguistic stability.
  • Notable differences emerged in feature salience and type across languages.
  • Domain comparisons revealed distinct patterns for natural versus artefact concepts.

Conclusions:

  • Semantic feature norms are largely stable but exhibit nuanced cross-linguistic variations.
  • Findings inform theories of semantic representation and multilingual communication.
  • Understanding these variations is crucial for cross-cultural interaction.