چکیده
مقدمه
پیش زمینه مطالعه
مروری بر مطالعات پیشین
روش
نتایج
بحث
محدودیت ها و تحقیقات آتی
منابع
Abstract
Introduction
Study background
Literature review
Method
Results
Discussion
Limitations and future research
References
چکیده
تحقیقات کمی مبتنی بر نظریه به چگونگی استفاده استراتژیک از رسانه های اجتماعی در روابط عمومی دولت از طریق یادگیری ماشینی می پردازد. برای پر کردن این شکاف، ما راهی برای بهینهسازی تحلیل رسانههای اجتماعی برای مدیریت مسائل و بحرانها با استفاده از چارچوب تئوری اسناد برای تجزیه و تحلیل ۳۶۰۸۶۱ توییت پیشنهاد میکنیم. به طور خاص، ما انتساب مسئولیت بحران مربوط به گسترش COVID-19 و روابط آن را به احساسات منفی شهروندان ایالات متحده در توییتر به مدت شش ماه (از 20 ژانویه تا 30 ژوئن 2020) بررسی کردیم. نتایج این مطالعه نشان داد که تجزیه و تحلیل رسانه های اجتماعی ابزار معتبری برای نظارت بر چگونگی تبدیل شدن شیوع COVID-19 از یک موضوع به یک بحران برای دولت ترامپ است. علاوه بر این، عدم پاسخگویی دولت فدرال و ناتوانی در مدیریت شیوع این بیماری منجر به مشارکت شهروندان و تشدید توییتهای منفی شد که کاخ سفید ترامپ را مقصر میدانست. مفاهیم نظری و عملی نتایج مورد بحث قرار می گیرد.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
Little theory-grounded research addresses how to use social media strategically in government public relations through machine learning. To fill this gap, we propose a way to optimize social media analytics to manage issues and crises by using the framework of attribution theory to analyze 360,861 tweets. In particular, we examined the attribution of crisis responsibility related to the spread of COVID-19 and its relations to the negative emotions of U.S. citizens on Twitter for six months (from January 20 to June 30, 2020). The results of this study showed that social media analytics is a valid tool to monitor how the spread of COVID-19 evolved from an issue to a crisis for the Trump administration. In addition, the federal government’s lack of response and inability to handle the outbreak led to citizens’ engagement and amplification of negative tweets that blamed the Trump White House. Theoretical and practical implications of the results are discussed.
Introduction
On January 21, 2020, the first case of the novel coronavirus disease (hereafter COVID-19) was confirmed in the United States in a man who had returned from Wuhan, China (Schumaker, 2020). In the early stage of the COVID-19 pandemic, the number of infections and deaths in the United States rose faster than in any other country worldwide (Elflein, 2021). Despite the declaration of a national emergency on March 13, 2020, the federal government in the U.S. struggled to cope with the public health disaster during the early phase of the COVID-19 pandemic (Diamond, 2020, April 16).
When catastrophic events strike, public sector organizations ought to protect affected citizens and rebuild the nation with immediate aid and relief (Broom & Sha, 2012). Generally, citizens expect a higher standard from their government than from private-sector organizations amid a public health disaster (Liu & Horsley, 2007). History has shown that catastrophic events which are poorly managed by governments can result in government crises (Chon, 2019).
Results and analyses
5.1. RQ1. Attribution of the crisis responsibility of COVID-19 crisis spread in the U.S
Among a total of 44,723 tweets mentioning the U.S. government, there were 43,172 (96.5%) HCR tweets and 1551 (3.5%) non-HCR tweets. The number of tweets mentioning China was 4353. Among these, there were 3864 (88.8%) HCR tweets and 489 (11.2%) non-HCR tweets. As our study interest is in high crisis attribution, we excluded non-HCR tweets from our analysis. Fig. 3 shows weekly aggregated HCR tweets toward the U.S. government and China.