The "Small World of Words" German Free-Association Norms

TL;DR

This paper introduces the largest German free-association norms dataset, enabling research in linguistics, psychology, and cross-cultural studies by providing comprehensive association data for 5,877 words.

Contribution

It presents the SWOW-DE dataset, filling a gap by offering extensive German free-association norms and demonstrating their utility across multiple psycholinguistic paradigms.

Findings

SWOW-DE norms predict lexical decision performance

SWOW-DE responses align with existing German resources

Cross-linguistic comparison reveals shared and language-specific patterns

Abstract

Free-association norms provide essential empirical data for investigating linguistic, semantic, and cultural phenomena in the cognitive sciences. Although large-scale norms exist for languages such as English, Dutch, Spanish, and Mandarin Chinese, no comparable resource has been available for German. To address this gap, we present free-association norms for 5,877 German cue words as part of the German version of the multilingual Small World of Words (SWOW) project. We describe the data collection procedures, participant characteristics, and our comprehensive preprocessing pipeline before introducing the resulting SWOW-DE data set. Using data from three established psycholinguistic paradigms, we show that SWOW-DE norms robustly predict performance in lexical decision tasks, relatedness judgments, and psycholinguistic word ratings. Furthermore, we demonstrate that SWOW-DE responses compare favorably with existing German resources and provide a preliminary cross-linguistic comparison revealing both shared and language-specific association patterns, highlighting promising directions for future research. Overall, SWOW-DE represents the largest collection of German free associations to date and offers a unique resource for linguistic, psychological, and cross-cultural research.