全球傳染病風險下的社交媒體訊息分享：Twitter社群的COVID-19貼文內容與超連結分析

新興傳染病的未知與不確定風險為人們帶來焦慮與恐懼，大量資訊在全球社交媒體分享與流傳，造成資訊疫病（infodemic）。本研究目的是探究COVID-19爆發初期，Twitter社群分享的超連結訊息來源與內容類型，收集2020年1月到3月Twitter的相關貼文542萬則，結合運算傳播與質化方法，分析貼文超連結指向哪些網站訊息來源，找出社群最常分享的單一超連結是哪種類型的內容，進而探討這些文本內容形構的意義。本研究發現Twitter社群最常見的訊息來源為社交媒體平臺、專業新聞網站、內容農場網站，這反映文字與影音內容的跨社交平臺傳播生態，全球或在地專業新聞仍是人們最常仰賴的訊息來源，內容農場網站則作為另類訊息來源。在COVID-19爆發初期，Twitter社群分享數高的超連結內容有四種主要類型：即時更新的疫情數據、吹哨者李文亮醫生之死的突發新聞、關於病毒起源疑似為生化武器的陰謀論、中國的對外宣傳。前二類是以事實為基礎的正確訊息，幫助公眾瞭解疫情最新進展與吹哨者死於疫病的公眾反應；後二類是社交媒體的運算宣傳，利用疫情期間人們的恐慌與焦慮心理，造就更多陰謀論流傳與中國宣傳的操作空間。

關鍵字

社交媒體；風險傳播；陰謀論；新冠肺炎；資訊疫病；運算宣傳

並列摘要

In December 2019 an unidentified type of pneumonia with strong contagiousness broke out in Wuhan, China (originally known as Wuhan pneumonia and later renamed as coronavirus disease 2019, COVID-19). The epidemic rapidly spread to the whole of China and surrounding countries by late January, 2020. The epidemic in China and Asian countries quickly aroused great concern and discussion among the global Chinese and international communities on social media. The unknown risk of highly contagious emerging diseases has deepened the anxiety and fear of people around the world to varying degrees. People share and spread a lot of information on social media, including news reports, public discussions, and even various false information or conspiracy theories. Emotions such as fear, anxiety, anger, etc. provide opportunities to people with intentions to use fear to manipulate false information. This resulted in an increasing amount of false information and conspiracy theories during the epidemic, harming the control of the epidemic and causing social media users to have information epidemics. This is called 'infodemic'. The World Health Organization and the United Nations jointly issued a statement in September 2020 stating that COVID-19 is the first pandemic in history in which technology and social media are being used on a massive scale to keep people safe, informed, and connected, but at the same time, it has caused a large-scale infodemic. People are faced with a surplus of information online and offline, such as the deliberate spreading of misinformation or falsehoods to undermine global public health works, to amplify hate speech, and to promote various conflicts. Such information epidemics endangered the control of COVID-19. Governments and organizations thus have to work better together to control an information epidemic. Bunker (2020) believes that the development of digital platforms controls the flow of information, but it also destroys the situational awareness shared by people. The cause of the infodemic is that people do not know who to trust, which leads to further anxiety and panic. The unknown and uncertain risks of COVID-19, an emerging infectious disease, have brought great anxiety and fear to people and also caused infodemic on social media. This study explores how the online community conducts information seeking and sharing behaviors on global social media when people face COVID-19. We take Twitter as a data collection platform and conduct hyperlink analysis to find the main information sources and types of information sought by the online community. Next, we analyze the discourse frameworks from the content of the hyperlinked messages cited by many users. Based on these reasons, this study explores how people seek and share information on social media during the crisis of an unknown infectious disease outbreak, especially where hyperlinks are shared and cited on social media. The main purpose of this paper is to answer the following three research questions. 1. In the early days of the COVID-19 outbreak, which information sources were hyperlinks, which ones were included in COVID-19-related tweets, and what type of domain websites were these sources? 2. Among the single hyperlinks most frequently shared, what types of articles or webpage content did these hyperlinks point to? What are the differences in the sharing behaviors among different types of hyperlinks? Continuing the above question, we explore the textual contents in various types of articles on most frequently shared COVID-19 related tweets. The meaning of the articles shared by the Twitter community during the outbreak as constructed to the audience will be understood through qualitative discourse analysis. For the methodology, this study combines a hybrid approach of online ethnography, computational communication methods, and qualitative discourse analysis. First, the topics of discussion in the Chinese Twitter community are observed through online ethnography. As the epidemic first broke out in Wuhan, the keywords for querying and collecting Twitter data are determined based on earlier online observations. Second, a huge amount of COVID-19 data on social media is collected through Twitter API. The hybrid media system connected by Twitter is explored by analyzing the hyperlinks included in the Twitter dataset, both computationally and manually. The domain websites of the hyperlinks are encoded to identify various types of websites, including professional news websites, YouTube channels, government websites, false information websites, and so on. Finally, qualitative discourse analysis is performed to understand the discourse structure and meaning of hyperlinked articles by intentional sampling the hyperlinked articles that have been shared more than 500 times on Twitter. This study's dataset covers 5.42 million COVID-19 related tweets from January to March 2020. Most of the tweets were in English (56%), followed by Spanish (17%), and the rest of the languages were all within 5%. We then analyze the types of websites pointed to by these hyperlinks, as well as the types of article content linked to them, using computational and manual methods. The findings show that the most shared information contents during the COVID-19 pandemic are mostly from social media platforms such as Twitter and YouTube, professional journalism websites including international media (Reuters and New York Times) and local media (South Chinese Morning Post and Yahoo News Japan), and content farm websites such as Zero Hedge. The most shared hyperlinks can be categorized into four different types: (1) real-time COVID-19 dashboards, such as COVID-19 Dashboard by CSSE at Johns Hopkins University; (2) breaking news, especially about the death of Dr. Li Wenliang, who was the whistle-blower of COVID-19; (3) conspiracy theories regarding the origins of the virus, implying it is a bioweapon; and (4) propaganda from the China government to present a good-China story. The four types of articles can be understood as fact-based, fiction, or semi-fact. The first two ((1) and (2)) are fact-based information aiming to help the public understand the pandemic, and the latter two ((3) and (4)) are politically motivated computational propaganda exploiting fear and anxiety among the public.

並列關鍵字

computational propaganda ； conspiracy theory ； COVID-19 ； infodemic ； risk communication ； social media

參考文獻

Bunker, D. (2020). Who do you trust? The digital destruction of shared situational awareness and the COVID-19 infodemic. International Journal of Information Management, 55. doi: 10.1016/j.ijinfomgt.2020.102201

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