Quantifying the moral narratives expressed in the user-generated text, news, or public discourses is fundamental for understanding individuals' concerns and viewpoints and preventing violent protests and social polarisation. The Moral Foundation Theory (MFT) was developed to operationalise morality in a five-dimensional scale system. Recent developments of the theory urged for the introduction of a new foundation, the Liberty Foundation. Being only recently added to the theory, there are no available linguistic resources to assess whether liberty is present in text corpora. Given its importance to current social issues such as the vaccination debate, we propose two data-driven approaches, deriving two candidate lexicons generated based on aligned documents from online news sources with different worldviews. After extensive experimentation, we contribute to the research community a novel lexicon that assesses the liberty moral foundation in the way individuals with contrasting viewpoints express themselves through written text. The LibertyMFD dictionary can be a valuable tool for policymakers to understand diverse viewpoints on controversial social issues such as vaccination, abortion, or even uprisings, as they happen and on a large scale.
翻译:将用户生成的文本、新闻或公共言论中表达的道德叙事进行量化,对于理解个人的关切和观点以及防止暴力抗议和社会两极化至关重要。道德基金会理论(MFT)是用来在一个五维规模的系统中操作道德的。理论的最近发展要求引入一个新的基础,即自由基金会。只是在最近才被添加到理论中,因此没有可用的语言资源来评估自由是否存在于文本中。鉴于自由对诸如疫苗接种辩论等当前社会问题的重要性,我们提出了两种数据驱动的方法,即根据不同世界观的在线新闻来源的一致文件产生两种候选词典。经过广泛的实验,我们为研究界贡献了一种新的词汇,用个人通过书面文本表达不同观点的方式评估自由道德基础。自由MFD字典可以成为决策者了解诸如疫苗接种、堕胎等有争议的社会问题的不同观点的宝贵工具。