论文标题
通过利用社会科学的衡量知识来改善立场检测：荷兰政治推文和传统性别角色部门的案例研究
Improving Stance Detection by Leveraging Measurement Knowledge from Social Sciences: A Case Study of Dutch Political Tweets and Traditional Gender Role Division
论文作者
论文摘要
立场检测（SD）涉及自动确定文本作者对目标的观点（即反对，反对或中立）的观点。 SD已应用于许多研究主题，其中对政治推文背后的立场的发现是重要的。在本文中，我们将SD应用于2017年至2021年期间荷兰官方党派账户的推文数据集，重点是对传统性别角色分区的立场，这是荷兰政党（某些）荷兰政党之间的分裂问题。为了实施和改善传统性别角色划分的SD，我们建议利用社会科学的既定调查工具，该工具已得到验证，目的是为了衡量对传统性别角色分裂的态度。基于我们的实验，我们表明，使用这种经过验证的调查工具有助于提高SD性能。
Stance detection (SD) concerns automatically determining the viewpoint (i.e., in favour of, against, or neutral) of a text's author towards a target. SD has been applied to many research topics, among which the detection of stances behind political tweets is an important one. In this paper, we apply SD to a dataset of tweets from official party accounts in the Netherlands between 2017 and 2021, with a focus on stances towards traditional gender role division, a dividing issue between (some) Dutch political parties. To implement and improve SD of traditional gender role division, we propose to leverage an established survey instrument from social sciences, which has been validated for the purpose of measuring attitudes towards traditional gender role division. Based on our experiments, we show that using such a validated survey instrument helps to improve SD performance.
