论文标题
Culturebert：通过基于变压器的语言模型来衡量企业文化
CultureBERT: Measuring Corporate Culture With Transformer-Based Language Models
论文作者
论文摘要
本文将基于变压器的语言模型引入了文献中的文献中，从文本文档中衡量了企业文化。我们编写了一个独特的数据集，包括人类评估者在评论揭示有关公司企业文化的信息方面标记的雇员评论。使用此数据集，我们调整了基于最新的变压器的语言模型来执行相同的分类任务。在样本外的预测中，我们的语言模型分类了17至30个百分点的员工评论比传统的文本分类方法要多于人类评估者。我们使我们的模型公开可用。
This paper introduces transformer-based language models to the literature measuring corporate culture from text documents. We compile a unique data set of employee reviews that were labeled by human evaluators with respect to the information the reviews reveal about the firms' corporate culture. Using this data set, we fine-tune state-of-the-art transformer-based language models to perform the same classification task. In out-of-sample predictions, our language models classify 17 to 30 percentage points more of employee reviews in line with human evaluators than traditional approaches of text classification. We make our models publicly available.
