data_comparing_semantic

To examine how the phonetic and semantic features of onomatopoeic words influence material perception, we conducted a semantic differentiation task with Turkish-speaking participants (N = 28) unfamiliar with Japanese. Stimuli consisted of three-word sets: 14 Turkish words, 14 semantically similar Japanese words, and 14 phonetically similar Japanese words. Participants rated each word on seven adjective pairs: (1) flat-bumpy, (2) warm-cold, (3) wet-dry, (4) light-heavy, (5) smooth-rough, (6) slippery-sticky, and (7) granular-whole. The data is winsorized to make it appropriate for our analyses. R codes for MDS analysis is also included.为探究拟声词的语音与语义特征对材料知觉（material perception）的影响，我们招募了28名母语为土耳其语且不熟悉日语的被试，开展了语义区分任务（semantic differentiation task）。实验刺激由三类词汇集合构成：14个土耳其语词汇、14个语义相似日语词汇以及14个语音相似日语词汇。被试需针对每个词汇在7组形容词对下完成评分，这7组形容词对分别为：(1) 平坦-凹凸不平、(2) 温暖-冰冷、(3) 湿润-干燥、(4) 轻盈-厚重、(5) 光滑-粗糙、(6) 滑腻-粘稠、(7) 颗粒状-完整。为适配后续分析的要求，我们对数据进行了缩尾处理（winsorization）。本数据集还附带用于多维尺度分析（Multidimensional Scaling, MDS）的R代码。