跨越边界而不越界：社会语言学意识如何优化面向西班牙语国家用户的本地化西班牙语AI模型的用户参与度
Crossing Borders Without Crossing Boundaries: How Sociolinguistic Awareness Can Optimize User Engagement with Localized Spanish AI Models Across Hispanophone Countries
AI总结：
本文通过分析拉美与西班牙西班牙语变体的社会语言学差异，论证地域敏感本地化AI模型的必要性，并提出至少五种西班牙语子变体以提升用户信任、包容性和国际化战略效果。
摘要：
大语言模型从定义上即以语言为基础。为了强调区域本地化模型的迫切需求，本文考察了拉丁美洲与西班牙之间书面西班牙语变体的主要差异，并对其进行了深入的社会文化和语言学语境化分析。我们认为，这些差异通过制造社会语言学上的不协调，实际上构成了不同方言群体在日常西班牙语使用中的显著鸿沟，以至于对地域敏感的AI模型将在弥合这些分歧方面发挥关键作用。通过这种方式，该方法为更好、更高效的本地化策略提供了依据，同时也有助于更充分地实现包容性目标，并在一个低风险投资的主要地理区域内确保持续的活跃日用户增长。因此，至少实施所提出的五种西班牙语子变体可以应对两条行动路线：培养用户对AI语言模型的信任和依赖，同时展示一种文化、历史和社会语言学层面的意识，这种意识将对任何国际化战略产生积极影响。
英文摘要：
Large language models are, by definition, based on language. In an effort to underscore the critical need for regional localized models, this paper examines primary differences between variants of written Spanish across Latin America and Spain, with an in-depth sociocultural and linguistic contextualization therein. We argue that these differences effectively constitute significant gaps in the quotidian use of Spanish among dialectal groups by creating sociolinguistic dissonances, to the extent that locale-sensitive AI models would play a pivotal role in bridging these divides. In doing so, this approach informs better and more efficient localization strategies that also serve to more adequately meet inclusivity goals, while securing sustainable active daily user growth in a major low-risk investment geographic area. Therefore, implementing at least the proposed five sub variants of Spanish addresses two lines of action: to foment user trust and reliance on AI language models while also demonstrating a level of cultural, historical, and sociolinguistic awareness that reflects positively on any internationalization strategy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
