This paper presents a study that sought to identify the dimensions of variation underlying a corpus of Internet texts, using Biber’s (1988) multi-dimensional (MD) analysis framework. The corpus was compiled following the method proposed by Biber (1993), according to which the size of each register subcorpus should be determined based on the linguistic variation across the texts. The corpus was tagged using the Biber Tagger and the features were counted and submitted to a factor analysis, which suggested three factors. The factors were interpreted as three dimensions of variation: involved, interactive discourse versus informational focus; expression of stance: interactional evidentiality; and expression of stance: interactional affect. The amount of register variation captured by the register distinctions on the dimensions ranged from 8.7% to 57.1%. Dimension 1 corroborate the oral/involved versus literate/informational distinction defined in previous MD studies of non-Internet registers, whereas Dimensions 2 and 3 highlight the important role played by stance in social media.

中文翻译：

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互联网注册的变化维度

本文提出了一项研究，该研究旨在使用 Biber (1988) 的多维 (MD) 分析框架确定互联网文本语料库中的变异维度。语料库是按照 Biber (1993) 提出的方法编制的，根据该方法，每个语域子语料库的大小应根据文本之间的语言变化来确定。使用 Biber Tagger 对语料库进行标记，并对特征进行计数并提交给因子分析，该分析提出了三个因子。这些因素被解释为三个维度的变化：参与、互动话语与信息焦点；立场表达：互动证据；和表达立场：互动影响。维度上的寄存器差异捕获的寄存器变化量从 8.7% 到 57。1%。维度 1 证实了先前非互联网注册的 MD 研究中定义的口头/参与与识字/信息区别，而维度 2 和 3 则强调了立场在社交媒体中发挥的重要作用。