arXiv:2502.12057cs.CLcs.CY2025-02ACL被引 46

用社会文化理论解决文化NLP中的方法论缺陷

Culture is Not Trivia: Sociocultural Theory for Cultural NLP

  • 引入社会文化语言学理论重构文化认知框架
  • 指出现有文化数据集存在静态、覆盖窄等问题
  • 建议以本地化为方向推动文化智能发展

文化自然语言处理领域近年快速发展,旨在确保语言技术在多元用户群体中有效且安全。然而,该领域缺乏统一的文化概念,普遍依赖多种文化代理指标,导致一系列共性局限:粗略的国家边界无法捕捉内部细微差异,数据集覆盖有限,仅涵盖少数高度代表性的文化,且缺乏动态性,使文化基准保持静态,无法随文化演变而更新。本文通过一篇立场论文指出,这些方法论问题本质上源于理论空白。我们借鉴社会文化语言学中成熟的文化理论,通过案例研究阐明其对方法约束与优势的解释力,提出具有理论依据的改进路径,主张将‘本地化’作为当前文化NLP工作的更合适目标框架。

原文摘要 · Abstract (English)

The field of cultural NLP has recently experienced rapid growth, driven by a pressing need to ensure that language technologies are effective and safe across a pluralistic user base. This work has largely progressed without a shared conception of culture, instead choosing to rely on a wide array of cultural proxies. However, this leads to a number of recurring limitations: coarse national boundaries fail to capture nuanced differences that lay within them, limited coverage restricts datasets to only a subset of usually highly-represented cultures, and a lack of dynamicity results in static cultural benchmarks that do not change as culture evolves. In this position paper, we argue that these methodological limitations are symptomatic of a theoretical gap. We draw on a well-developed theory of culture from sociocultural linguistics to fill this gap by 1) demonstrating in a case study how it can clarify methodological constraints and affordances, 2) offering theoretically-motivated paths forward to achieving cultural competence, and 3) arguing that localization is a more useful framing for the goals of much current work in cultural NLP.

文化NLP社会文化本地化

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