对比人类与大模型对英文拼写变异的社交感知差异。
Social Perceptions of English Spelling Variation on Twitter: A Comparative Analysis of Human and LLM Responses
- 采用社会语言学方法，比较人与大模型对拼写变异的评分。
- 人类与大模型在正式度、谨慎度、年龄感上相关性高，但分布差异明显。
- 揭示大模型社交感知局限，适合研究人机认知差异的学者参考。
拼写变异（如 funnnn 与 fun）会影响文本及作者的社交感知：我们常对不同书写形式产生各种联想（文本是否非正式？作者是否年轻？）。本研究聚焦英文在线写作中的拼写变异社交感知，探究人类与大型语言模型（LLMs）的感知一致性。基于社会语言学方法，我们比较了人类与大模型在三个关键社交属性（正式度、谨慎度、年龄感）上的评分。结果显示，人类与大模型评分整体相关性较强，但在评分分布及不同拼写变异类型间的比较中存在显著差异。
原文摘要 · Abstract (English)
Spelling variation (e.g. funnnn vs. fun) can influence the social perception of texts and their writers: we often have various associations with different forms of writing (is the text informal? does the writer seem young?). In this study, we focus on the social perception of spelling variation in online writing in English and study to what extent this perception is aligned between humans and large language models (LLMs). Building on sociolinguistic methodology, we compare LLM and human ratings on three key social attributes of spelling variation (formality, carefulness, age). We find generally strong correlations in the ratings between humans and LLMs. However, notable differences emerge when we analyze the distribution of ratings and when comparing between different types of spelling variation.
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