From semantic knowledge to semantic features: French semantic feature production norms for 360 concepts

Area of Science:

• Cognitive Psychology
• Linguistics
• Neuroscience

Background:

• Empirically derived semantic feature norms are crucial for studying semantic memory and cognition.
• Existing norms are available for many languages, but not for native French speakers.
• This gap limits research on semantic cognition within the French-speaking population.

Purpose of the Study:

• To create a comprehensive set of semantic feature production norms for French concepts.
• To provide a valuable resource for researchers investigating semantic memory and cognition in French.
• To facilitate the development of assessment tools for semantic disorders in French.

Main Methods:

• Collected feature data from 580 young French-speaking adults for 360 concepts.
• Participants completed a property generation task, listing features for each concept.
• Unified participant productions to compile 4586 unique semantic features.

Main Results:

• Developed semantic feature norms for 360 French concepts across diverse semantic categories.
• Calculated various semantic indexes, including richness (e.g., number of features) and informativeness (e.g., cue validity).
• Organized the norms into four openly accessible datasets: concept-feature, concept, concept-concept matrix, and feature-feature matrix.

Conclusions:

• The newly developed French semantic feature norms are a significant resource for cognitive science.
• These norms will aid researchers in exploring normal and impaired semantic cognition in French.
• The openly available datasets support diverse research methodologies in semantic memory studies.