Lahnakoski Juha M, Bennett Ellie, Nummenmaa Lauri, Steinert Ulrike, Sams Mikko, Svärd Saana
Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Center Jülich, Jülich, Germany.
Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
iScience. 2024 Dec 4;27(12):111365. doi: 10.1016/j.isci.2024.111365. eCollection 2024 Dec 20.
Emotions are associated with subjective emotion-specific bodily sensations. Here, we utilized this relationship and computational linguistic methods to map a representation of emotions in ancient texts. We analyzed Neo-Assyrian texts from 934-612 BCE to discern consistent relationships between linguistic expressions related to both emotions and bodily sensations. We then computed statistical regularities between emotion terms and words referring to body parts and back-projected the resulting emotion-body part relationships on a body template, yielding bodily sensation maps for the emotions. We found consistent embodied patterns for 18 distinct emotions. Hierarchical clustering revealed four main clusters of bodily emotion categories, two clusters of mainly emotions, one large cluster of mainly emotions, and one of and . These results reveal the historical use of embodied language pertaining to human emotions. Our data-driven tool could enable future comparisons of textual embodiment patterns across different languages and cultures across time.
情感与特定情感的主观身体感觉相关联。在此，我们利用这种关系和计算语言学方法来绘制古代文本中情感的表征。我们分析了公元前934年至612年的新亚述文本，以辨别与情感和身体感觉相关的语言表达之间的一致关系。然后，我们计算了情感术语与指代身体部位的词汇之间的统计规律，并将由此产生的情感 - 身体部位关系反向投影到身体模板上，生成情感的身体感觉图谱。我们发现了18种不同情感的一致具身模式。层次聚类揭示了身体情感类别的四个主要聚类，两个主要为[此处原文缺失具体情感类别]情感的聚类，一个主要为[此处原文缺失具体情感类别]情感的大聚类，以及一个[此处原文缺失具体情感类别]和[此处原文缺失具体情感类别]的聚类。这些结果揭示了与人类情感相关的具身语言的历史用法。我们的数据驱动工具能够使未来跨时间对不同语言和文化中的文本具身模式进行比较。
