تعد عملية التعدين أسباب صنع القرار السياسي مجالا نشطا في مجال العلوم السياسية. في الماضي، ركزت معظم الدراسات على السياسات طويلة الأجل التي يتم جمعها على مدى عدة عقود من الزمن، وقد اعتمدت في المقام الأول على المسوحات كمصدر رئيسي للتنبؤ. ومع ذلك، فإن جائحة Covid-19 الأخير قد أدى إلى ظاهرة سياسية جديدة، حيث يتكون عملية صنع القرار السياسي من قرارات قصيرة الأجل المتكررة، كلها على نفس الموضوع السيطرة --- الوباء. في هذه الورقة، نركز على مسألة كيفية تأثير الرأي العام على قرارات السياسة، أثناء السيطرة على الخبراء مثل الزيادات في حالة Covid-19 أو معدلات البطالة. باستخدام مجموعة بيانات تتكون من بيانات تويتر من الولايات الأمريكية 50، نقوم بتصنيف المشاعر تجاه محافظي كل دولة، وإجراء الدراسات والمقارنات التي تسيطر عليها. بناء على العينات المترجمة من المشاعر والسياسات والخلفية، نقوم بإجراء استنتاج سببي لاكتشاف الاتجاهات في اتخاذ القرارات السياسية في جميع الدول المختلفة.
Mining the causes of political decision-making is an active research area in the field of political science. In the past, most studies have focused on long-term policies that are collected over several decades of time, and have primarily relied on surveys as the main source of predictors. However, the recent COVID-19 pandemic has given rise to a new political phenomenon, where political decision-making consists of frequent short-term decisions, all on the same controlled topic---the pandemic. In this paper, we focus on the question of how public opinion influences policy decisions, while controlling for confounders such as COVID-19 case increases or unemployment rates. Using a dataset consisting of Twitter data from the 50 US states, we classify the sentiments toward governors of each state, and conduct controlled studies and comparisons. Based on the compiled samples of sentiments, policies, and confounders, we conduct causal inference to discover trends in political decision-making across different states.
References used
https://aclanthology.org/
We present machine learning classifiers to automatically identify COVID-19 misinformation on social media in three languages: English, Bulgarian, and Arabic. We compared 4 multitask learning models for this task and found that a model trained with En
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 analysi
With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic. Fighting this infodemic has been declared one of the mo
In online forums focused on health and wellbeing, individuals tend to seek and give the following social support: emotional and informational support. Understanding the expressions of these social supports in an online COVID- 19 forum is important fo
The COVID-19 pandemic has spawned a diverse body of scientific literature that is challenging to navigate, stimulating interest in automated tools to help find useful knowledge. We pursue the construction of a knowledge base (KB) of mechanisms---a fu