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Register a new userStatistically Evaluating Social Media Sentiment Trends towards COVID-19 Non-Pharmaceutical Interventions with Event Studies
تقييم إحصائيا اتجاهات معنويات وسائل التواصل الاجتماعي نحو التدخلات غير الدوائية CovID-19 مع دراسات الأحداث
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في خضم الوباء العالمي، فهم رأي الجمهور في تدخلات حكومتهم على مستوى السياسة، وغير الدوائية (NPIS) هو عنصر حاسم في عملية صنع السياسات الصحية. عملت العمل المسبق في تحليل معنويات NPI CoviD-19 من قبل المجتمع الوبائي دون إحدى طرق تنسب المعنويات بشكل صحيح على الأحداث، وهي القدرة على التمييز بين تأثير مختلف الأحداث عبر الزمن، وهو نموذج متماسك للتنبؤ برأي الأحداث المستقبلية في المستقبل نفس النوع، ولا حتى وسيلة لإجراء اختبارات الأهمية. نقول هنا أن طريقة التقييم التي كانت حاجة ماسة إليها موجودة بالفعل. في القطاع المالي، دراسات الأحداث التقلبات في سعر الأسهم في شركة تداول الجمهور شائعة لتحديد آثار إعلانات الأرباح، ومواضع المنتجات، وما إلى ذلك. الطريقة نفسها مناسبة لتحليل تباين المشاعر الزمنية في ضوء NPIS على مستوى السياسة وبعد نحن نقدم دراسة حالة عن شعور تويتر تجاه NPIS على مستوى السياسات في كندا. تؤكد نتائجنا على اتصال إيجابي عموما بين إعلانات NPIS ومعنويات تويتر، ونحن نوثق ارتباطا واعدا بين نتائج هذه الدراسة والمسح الصحي العام للامتثال الشعبي للمنظمات غير الحكومية.
In the midst of a global pandemic, understanding the public's opinion of their government's policy-level, non-pharmaceutical interventions (NPIs) is a crucial component of the health-policy-making process. Prior work on CoViD-19 NPI sentiment analysis by the epidemiological community has proceeded without a method for properly attributing sentiment changes to events, an ability to distinguish the influence of various events across time, a coherent model for predicting the public's opinion of future events of the same sort, nor even a means of conducting significance tests. We argue here that this urgently needed evaluation method does already exist. In the financial sector, event studies of the fluctuations in a publicly traded company's stock price are commonplace for determining the effects of earnings announcements, product placements, etc. The same method is suitable for analysing temporal sentiment variation in the light of policy-level NPIs. We provide a case study of Twitter sentiment towards policy-level NPIs in Canada. Our results confirm a generally positive connection between the announcements of NPIs and Twitter sentiment, and we document a promising correlation between the results of this study and a public-health survey of popular compliance with NPIs.
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