AI 中文总结
本研究探索用知识图谱等语义建模方法替代文本，以非文本方式表征社会文化人类学知识，挑战文本主导地位并开辟新的认识论路径。
AI 中文摘要
本研究考察了语义网和关联数据背景下知识表征这一新兴领域，重点关注社会科学——尤其是社会文化人类学——所产出的知识。研究始于这样一个前提：自然语言，尤其是其文本化形式，长期以来一直是生产和传播人类学研究的主要载体。在信息科学理论方法的启发下，本研究探讨了计算方法如何为构建和表征人类学知识提供替代模式。它挑战了文本作为唯一表征媒介的主导地位，并强调了语义建模在开辟新的认识论路径方面的潜力。同时，研究也承认了这一转变所涉及的概念和方法论挑战。这种方法将重点从指标和编程上转移开，突出概念化、语义、意义和推理过程，将其作为在数字环境中参与人类学知识的关键。
英文摘要
The study examines the emerging field of knowledge representation in the context of the semantic web and linked data, with a focus on knowledge produced within the social sciences - particularly in sociocultural anthropology. It starts from the premise that natural language, especially its textualized form, has long been the primary vehicle for producing and communicating anthropological research. Informed by theoretical approaches from information science, the study explores how computational methods may offer alternative modes of structuring and representing anthropological knowledge. It challenges the dominance of text as the sole representational medium and highlights the potential of semantic modeling to open new epistemological pathways. At the same time, it acknowledges the conceptual and methodological challenges involved in such a transition. This approach shifts emphasis away from metrics and programming, foregrounding processes of conceptualization, semantics, meaning, and reasoning as key to engaging with anthropological knowledge in digital environments.
Comments19 pages, 2 figures
Journal refPeponakis, M., Kapidakis, S., Doerr, M., & Tountasaki, E. (2026). Toward non-textual representation of social anthropology: Modeling cultures as knowledge graphs. Journal of Digital Social Research, 8(1), 68-86
