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    Title: 社群媒體災難新聞報導與閱聽人留言情緒之研究:以俄烏戰爭為例
    Emotions of Audience Comments towards Disaster Reporting on Social Media: Case Study of Russia-Ukraine War
    Authors: 江曉琳
    Kwong, Hiu-Lam
    Contributors: 許志堅
    Sheu, Jyh-Jian
    江曉琳
    Kwong, Hiu-Lam
    Keywords: 俄烏戰爭
    災難傳播
    情緒反應
    社群媒體新聞
    厚數據分析
    Russia-Ukraine War
    disaster communication
    emotional responses
    social media news
    thick data analysis
    Date: 2024
    Issue Date: 2024-03-01 13:50:50 (UTC+8)
    Abstract:   2022年2月,俄羅斯正式宣布向烏克蘭展開軍事行動,俄烏戰爭隨即爆發,戰事至今造成多人死傷,烏克蘭當地飽受戰火摧殘,生靈塗炭、民不聊生。由於俄烏關係與台海兩岸的歷史脈絡具有相似點,俄烏戰爭受到台灣社會廣泛重視,部分支持者打著「今日烏克蘭,明日台灣」的旗號,呼籲民眾關注戰爭局勢並聲援烏克蘭。烏克蘭總統澤倫斯基亦憑著抵抗敵國的決心,獲美國《時代》雜誌選為2022年的風雲人物。
      本研究以俄烏戰爭作為一個災難的例子,結合大數據和人工介入的厚數據方法,分析社群媒體上的戰亂新聞報導及閱聽人的情緒反應。本研究從六家台灣媒體的Facebook新聞粉專(包括《中國時報》、《聯合報》、《自由時報》、《東森電視》、《三立電視》及《TVBS》)蒐集俄烏戰爭相關報導貼文與留言,首先進行大數據的資料統計;接下來,本研究從資料出篩選出「俄烏戰爭局勢發展」與「澤倫斯基相關議題」等兩個議題的報導貼文,以厚數據方法進行新聞主題類目、情緒類型及情緒表達對象之分類,旨在以戰爭階段、新聞主題、個別媒體等三個維度,比較閱聽人的情緒反應差別。
      本研究的分析結果指出,俄烏戰爭的新聞報導主要集中在戰爭初期,儘管過後有個別重要事件使報導數量一度急升,仍然無法達至戰爭初期的水平。不論在戰爭的哪個階段,「嘲諷」仍然是最主要的閱聽人情緒反應,當中在「俄烏戰爭局勢發展」的報導下,閱聽人普遍對烏克蘭感「熱情」、對俄羅斯感「憤怒」。在新聞主題方面,大部分主題依舊由「嘲諷」情緒主導,對象則根據主題而定。研究比較不同媒體的閱聽人情緒反應後發現,閱聽人可分為「順應政府立場」和「抗拒政府立場」兩類型,前者可見於「泛綠」或「中立」為主要受眾的媒體,在戰爭中支持烏克蘭一方;後者可見於「泛藍」受眾為主的媒體,傾向對烏克蘭冷嘲熱諷。
      In February 2022, Russia officially announced the special military operation in Ukraine, which indicated the outbreak of Russia-Ukraine War. Since then, the warfare has caused thousands of people to get injured, lose their home, and even get killed. On the other side of the world, people in Taiwan are paying attention to the war because there are similarities in historical contexts between Russia-Ukraine and Taiwan Strait relationships. Some supporters aim at pursuing others to focus on the war, by pointing out “Today’s Ukraine, tomorrow’s Taiwan”. Volodymyr Zelenskyy, the President of Ukraine, has been elected as Person of the Year by Time magazine in 2022, muchly due to his determination to protect his country from invasion.
      Taking Russia-Ukraine War as a disaster example, this research aims at analyzing war news reports and emotional responses of audience on social media, by a combination of big data and thick data methodologies. Such news reports and comments have been collected from six Taiwanese media, including ChinaTimes, United Daily News, Liberty Times, Eastern Television, Sanlih Television and TVBS. At first, big data analysis has been performed. Then, two issues, “Russia-Ukraine War development” and “Zelenskyy-related topic”, has been selected for further thick data analysis, which includes identifying news themes, types of emotion and targets of emotion expressed. At the end, differences of audience’s emotions can be compared by using stage-of-war, news theme and media dimensions.
      Results reveal that news reports of Russia-Ukraine War concentrate at the early stages of war. Although the number of reports surged up occasionally during the progress, it cannot reach the same level at the early stages. From the stage-of-war dimension, “satire” is the major emotional responses of audience in every stage of war. On the issue of “Russia-Ukraine War development”, audience feel “enthusiastic” towards Ukraine and “angry” towards Russia in general. Speaking of news theme, “satire” is still the dominating emotion, and the targets of emotion expressed depend on themes. By comparing emotional responses in different media, this research identifies two types of audience: “conformist” and “resistists”. Conformists join government’s stance to support Ukraine, and are probably the audience of pan-Green or neutral media. On the other hand, resistists tend to be readers of pan-Blue media, and they usually satirize the situation in Ukraine.
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