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.

翻译：自由联想常模为认知科学中研究语言、语义及文化现象提供了关键的经验数据。尽管英语、荷兰语、西班牙语和普通话等语言已存在大规模常模，但德语至今缺乏类似资源。为填补这一空白，我们作为多语言"词汇小世界"（SWOW）项目德语版本的一部分，发布了5,877个德语提示词的自由联想常模。我们详细描述了数据收集流程、参与者特征以及全面的预处理管线，随后介绍了生成的SWOW-DE数据集。利用三个成熟心理语言学范式的数据，我们证明SWOW-DE常模能稳健预测词汇决策任务、关联性判断任务及心理语言学词汇评分中的表现。此外，我们展示了SWOW-DE响应与现有德语资源的优势对比，并通过初步跨语言比较揭示了共享与语言特异性关联模式，为未来研究指明了有前景的方向。总体而言，SWOW-DE是迄今为止规模最大的德语自由联想集合，为语言学、心理学及跨文化研究提供了独特资源。