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Register a new userAn unsupervised framework for tracing textual sources of moral change
إطار عمل غير مخالف لتتبع مصادر نصية من التغيير الأخلاقي
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تلعب الأخلاق دورا مهما في الرفاه الاجتماعي، لكن تصور الناس الأخلاقي ليس مستقرا وتتغير مع مرور الوقت. أظهرت التطورات الحديثة في معالجة اللغة الطبيعية أن النص هو وسيلة فعالة لإبلاغ التغيير الأخلاقي، ولكن لم تبذل أي محاولة لتحديد أصول هذه التغييرات. نقدم إطارا غير مؤظفي رواية لتتبع مصادر نصية من التغيير الأخلاقي نحو الكيانات عبر الزمن. نورد التغيير الأخلاقي مع توزيعات موضعية الاحتمالية والنتائج النص المصدر الذي يمارس تأثيرا بارزا على دورة الوقت الأخلاقي. نقوم بتقييم إطار عملنا على مجموعة متنوعة من البيانات تتراوح من وسائل التواصل الاجتماعي إلى مقالات إخبارية. نظير على أن إطارنا لا يجسد الأحكام الأخلاقية البشرية المحبوبة فقط، ولكنه يحدد أيضا موضوعات المصدر المتماسك للتغيير الأخلاقي الناجم عن الأحداث التاريخية. نحن نطبق منهجيةنا لتحليل الأخبار في جائحة CovID-19 وإظهار فائدتها في تحديد مصادر التغيير الأخلاقي في الأحداث الاجتماعية عالية التأثير في الوقت الفعلي.
Morality plays an important role in social well-being, but people's moral perception is not stable and changes over time. Recent advances in natural language processing have shown that text is an effective medium for informing moral change, but no attempt has been made to quantify the origins of these changes. We present a novel unsupervised framework for tracing textual sources of moral change toward entities through time. We characterize moral change with probabilistic topical distributions and infer the source text that exerts prominent influence on the moral time course. We evaluate our framework on a diverse set of data ranging from social media to news articles. We show that our framework not only captures fine-grained human moral judgments, but also identifies coherent source topics of moral change triggered by historical events. We apply our methodology to analyze the news in the COVID-19 pandemic and demonstrate its utility in identifying sources of moral change in high-impact and real-time social events.
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