De Deyne Simon, Verheyen Steven, Ameel Eef, Vanpaemel Wolf, Dry Matthew J, Voorspoels Wouter, Storms Gert
University of Leuven, Leuven, Belgium.
Behav Res Methods. 2008 Nov;40(4):1030-48. doi: 10.3758/BRM.40.4.1030.
Features are at the core of many empirical and modeling endeavors in the study of semantic concepts. This article is concerned with the delineation of features that are important in natural language concepts and the use of these features in the study of semantic concept representation. The results of a feature generation task in which the exemplars and labels of 15 semantic categories served as cues are described. The importance of the generated features was assessed by tallying the frequency with which they were generated and by obtaining judgments of their relevance. The generated attributes also featured in extensive exemplar by feature applicability matrices covering the 15 different categories, as well as two large semantic domains (that of animals and artifacts). For all exemplars of the 15 semantic categories, typicality ratings, goodness ratings, goodness rank order, generation frequency, exemplar associative strength, category associative strength, estimated age of acquisition, word frequency, familiarity ratings, imageability ratings, and pairwise similarity ratings are described as well. By making these data easily available to other researchers in the field, we hope to provide ample opportunities for continued investigations into the nature of semantic concept representation. These data may be downloaded from the Psychonomic Society's Archive of Norms, Stimuli, and Data, www.psychonomic.org/archive.
在语义概念研究中，特征是许多实证和建模工作的核心。本文关注自然语言概念中重要特征的界定，以及这些特征在语义概念表征研究中的应用。文中描述了一项特征生成任务的结果，该任务以15个语义类别的示例和标签作为线索。通过统计生成特征的频率以及获取对其相关性的判断，来评估所生成特征的重要性。所生成的属性还出现在涵盖15个不同类别以及两个大语义领域（动物和人造物领域）的大量示例与特征适用性矩阵中。对于15个语义类别的所有示例，还描述了典型性评级、优度评级、优度排序、生成频率、示例联想强度、类别联想强度、估计习得年龄、词频、熟悉度评级、可想象性评级以及成对相似性评级。通过使该领域的其他研究人员能够轻松获取这些数据，我们希望为继续探究语义概念表征的本质提供充足的机会。这些数据可从心理onomic学会的规范、刺激和数据存档库（www.psychonomic.org/archive）下载。
