In this paper, we apply Item Response Theory, popular in education and political science research, to the analysis of argument persuasiveness in language. We empirically evaluate the model's performance on three datasets, including a novel dataset in the area of political advocacy. We show the advantages of separating these components under several style and content representations, including evaluating the ability of the speaker embeddings generated by the model to parallel real-world observations about persuadability.

翻译：在本文中,我们运用在教育和政治科学研究中流行的“项目反应理论”来分析语言中的说服力,我们从经验上评价该模型在三个数据集方面的表现,包括政治倡导领域的新数据集,我们展示了将这些组成部分分为几个风格和内容表述的优点,包括评价该模型所产生的演讲者嵌入对可感性进行平行现实世界观察的能力。