Head, The Functor Lab, Department of Cognitive and Brain Science, Ben-Gurion University of the Negev, Beer-Sheva, 84105, Israel.
Gilasio coding, Tel-Aviv, Israel.
Sci Data. 2023 Jul 29;10(1):505. doi: 10.1038/s41597-023-02406-6.
It has been realized that situational dimensions, as represented by human beings, are crucial for understanding human behavior. The Riverside Situational Q (RSQ) is a tool that measures the psychological properties of situations. However, the RSQ-4 includes only 90 items and may have limited use for researchers interested in measuring situational dimensions using a computational approach. Here we present a corpus of 10,000 artificially generated situations corresponding mostly with the RSQ-4. The dataset was generated using GPT, the state-of-the-art large language model. The dataset validity is established through inter-judge reliability, and four experiments on large datasets support its quality. The dataset and the code used for generating 100 situational dimensions may be useful for researchers interested in measuring situational dimensions in textual data.
人们已经意识到，代表人类的情境维度对于理解人类行为至关重要。Riverside 情境问卷 (RSQ) 是一种衡量情境心理特性的工具。然而，RSQ-4 仅包含 90 个项目，对于那些有兴趣使用计算方法来测量情境维度的研究人员来说，可能用途有限。在这里，我们提供了一个由 10000 个人工生成的情境组成的语料库，这些情境主要与 RSQ-4 相对应。该数据集是使用最先进的大型语言模型 GPT 生成的。数据集的有效性通过评委间的可靠性来建立，并且四个关于大型数据集的实验支持了其质量。该数据集和用于生成 100 个情境维度的代码可能对有兴趣在文本数据中测量情境维度的研究人员有用。
