揭示文化数据建模中的语义复杂性，警示评估误区
Semiotic Complexity and Its Epistemological Implications for Modeling Culture
- 将文化建模视为跨语言与数学域的翻译过程
- 指出主流评估方法错误地简化了语义复杂的文本
- 呼吁研究者提升建模的哲学自觉与解释透明度
计算人文学科亟需更深入的方法论探讨以实现认识论与解释上的清晰，推动领域成熟。本文将建模工作视作文化语言领域向计算数学领域及其反向的翻译过程。如同译者需反思翻译机制，计算人文学家也应明确自身建模逻辑，以保障内在一致性、避免隐蔽但关键的翻译误差，并促进解释透明性。本文提出‘语义复杂性’概念，即文本意义在不同解读视角下的可变程度，指出当前主流建模实践——尤其是评估方式——存在重大翻译错误：为追求表面清晰，将本具高度语义复杂性的数据当作简单处理。我们进一步提出若干建议，帮助研究者在工作中更充分回应此类认识论问题。
原文摘要 · Abstract (English)
Greater theorizing of methods in the computational humanities is needed for epistemological and interpretive clarity, and therefore the maturation of the field. In this paper, we frame such modeling work as engaging in translation work from a cultural, linguistic domain into a computational, mathematical domain, and back again. Translators benefit from articulating the theory of their translation process, and so do computational humanists in their work -- to ensure internal consistency, avoid subtle yet consequential translation errors, and facilitate interpretive transparency. Our contribution in this paper is to lay out a particularly consequential dimension of the lack of theorizing and the sorts of translation errors that emerge in our modeling practices as a result. Along these lines we introduce the idea of semiotic complexity as the degree to which the meaning of some text may vary across interpretive lenses, and make the case that dominant modeling practices -- especially around evaluation -- commit a translation error by treating semiotically complex data as semiotically simple when it seems epistemologically convenient by conferring superficial clarity. We then lay out several recommendations for researchers to better account for these epistemological issues in their own work.
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