網際網路興起與行動裝置普及後，人們越來越容易在各大社群媒體、討論區留下評論。其中，本來就影響甚大的負面口碑，結合了網路驚人的散步速率和廣大接觸群眾的特性，轉變為影響更為巨大的網路負面口碑。 過往有許多針對負面口碑的研究，這些研究大多面向一般企業，卻鮮少有研究針對公眾人物。然而，同時也有許多研究指出，許多企業會與公眾人物合作，而公眾人物自身做為容易被社會關注的目標，負面口碑有可能對其職業生涯與形象造成不良影響，故希望能針對網路負面口碑之於公眾人物的留言動機、內容以及解決方式研究。 本研究著重個案分析，我們將從PTT，全台灣知名的網路討論板，找尋針對個案中公眾人物評論，並且分析留言的措辭與內容，歸納留言者的動機、該負面留言的內容類型。並從網路上蒐集該公眾人物處理該負面網路口碑的資訊，分析其策略。 最終，本研究將歸納整理出動機、留言內容與公眾人物使用的策略，為未來在這塊學術領域有興趣繼續研究的同好們提供一個基礎，並為公眾人物以及其公關團隊避免與解決網路負面口碑提供建議與方針。 / Since the rise of social media and the spread of mobile devices, sharing comments, advice and information with people on the internet without the constraints of time and space has become part of modern life and has resulted in major changes to how people receive information. Because of these changes, one particular issue has become more important than before: the influence of electronic word of mouth (EWOM), especially the negative type. Word of mouth has long been a topic of research, and researchers have found that negative word of mouth (NWOM) can have a greater impact than positive or neutral word of mouth. Furthermore, EWOM can spread faster and wider than traditional WOM. Thus, if negative word of mouth were spread via electronic channels such as social media on internet, it can cause unimaginable damage to the target individual or organization. To date, few studies focus on public figures’ negative EWOM. However, public figures play important roles in many areas because of their high attention from society and may sometimes be the target of negative EWOM. Based on the above, this study seeks answers to the following questions: Why do people on the internet reply negatively to the target public figures (negative EWOM motivation)? What types of negative content do people on the internet generate toward the public figures? What types of strategies may be applied to deal with different types of negative EWOM and negative EWOM motivation more frequently? This study first searched and reviewed previous literature related to NWOM, EWOM and public figures and categorized a few motivation, types of negative content and strategies. We then chose twenty case studies, and collected comments about these twenty cases on PTT, the largest terminal-based bulletin board system (BBS) based in Taiwan. Based on the using words of these comments, we can find out new motivation and new types of negative content did not exist in previous literature. Furthermore, we tracked how these public figures deal with NWOM, and tried to find out new patterns of strategies. The research results can help managers and researchers prevent crises caused by negative EWOM or take appropriate approaches for these crises. Keywords: Negative Word of Mouth, Electronic Word of Mouth, Public Figures

行銷業者對負面口碑的負面影響已有所共識，它可能直接影響消費者對其產品或服務的知覺價值判斷，進而影響產品評價及購買行為。過往研究將負面口碑區分為理由型和情感型兩類，同時，負面口碑中所包含的訊息可能為產品或服務的主要或次要因素，因而在重要程度上存在差異。此外，考慮到消費者決策情境的不同，本研究以為自己或他人做選擇的方式喚起個體的短期自我構念，探討個體特徵在負面口碑對消費者態度與行為傾向影響過程中的調節效果。另，消費者在處理負面口碑時，可能會對其產生原因進行歸納推理，且存在歸因於產品或服務和口碑產製者兩種認知路徑，不同的歸因模式進而又會影響消費者的產品評價、購買意願等面向。因此，本研究旨在探討負面口碑訊息類型如何影響消費者的態度與行為傾向，並考量負面口碑重要程度和自我構念的調節作用，以及在此過程中歸因模式的可能中介效果。 本研究通過內容分析法在實務場域觀察負面口碑訊息類型，初步探討負面口碑訊息類型與產品評價之間的關係。其後，以兩個實驗設計驗證研究假設，實驗一為2（負面口碑訊息類型：理由型vs.情感型）×2（負面口碑重要程度：主要因素vs.次要因素）的二因子受試者間設計，實驗二則為2（負面口碑訊息類型：理由型vs.情感型）×2（負面口碑重要程度：主要因素vs.次要因素）×2（自我構念：獨立型vs.互依型）的三因子組間設計。研究發現：（一）相較於情感型負面口碑，理由型負面口碑對消費者態度與行為傾向的影響更為顯著。（二）負面口碑重要程度具顯著干擾作用，亦即，當負面口碑重要程度為主要因素時，理由型評論所產生的訊息可信度顯著高於情感型評論。（三）在負面口碑訊息類型、負面口碑重要程度對訊息可信度的影響過程中，歸因模式具有顯著的中介效果。（四）自我構念與負面口碑訊息類型具有交互作用，並連同負面口碑重要程度存在三階交互效果。本研究期望通過負面口碑影響機制理論模型的提出與驗證，對負面口碑傳播效果研究有所貢獻，同時，在實務上為行銷業者管理負面口碑提供參考。

口碑一直以為都是企業行銷的重要利器，而同時也是要害之一，且隨著網路的發達和社群網路的發展，對企業的影響也越來越大。而近幾年在媒體中開始出現一個新名詞，用來形容負面口碑在社群媒體中傳播的現象-線上口碑風暴(Online Firestorm)。 線上口碑風暴的相關研究相當的稀少，而在許多口碑的相關研究中也未多著墨，但隨著社群媒體的發展，此現象已越來越普遍，因此有研究探討的價值，所以在本研究中將先定義出線上口碑風暴，並以Google搜尋趨勢設計出測量線上口碑風暴的方式，以利將其從負面口碑的傳播分辨出來，並利用這樣的方法找出六個線上口碑風暴的個案來進行研究，配合Coombs的印象修復理論來進一步分析。 研究結果發現，可以將線上口碑風暴依成因分成「過去不好的服務或產品體驗」、「錯誤的時機情境」和「不適當的聲明或宣傳」，而各類別的最佳回應策略在文中有詳細講述。另外，當企業使用的回應策略越多時，線上口碑風暴持續的時間就可能越久。影響線上口碑風暴的因素有很多，經本研究的討論分析後，發現「負面訊息傳播的平台」、「回應策略的運用」和「企業的規模和性質」為最會影響線上口碑風暴的因素。 / Word-of-Mouth (WOM) has been a major marketing tool to the enterprise, but could also be one of its threats. With the development of the Internet and social networks, the impact of WOM on enterprises is also growing. In recent years, the rapid propagation of negative Word-of-Mouth in social media has gained much attention in media and is named “Online Firestorm.” Academic studies about Online Firestorm are rare, and researchers of Word-of-Mouth have not investigated it. Giving the development of social media, this phenomenon has become increasingly common. Therefore it is important for companies to know and better handle it and for researchers to investigate this new issue. In this study, we will define and measure Online Firestorm though Google Trends. We will also collect data from six cases and analyze how different responding strategies may result in different outcomes. Research found that Online Firestorm can be categorized into “past bad service or prouduct experience”, “bad timing scenarios” and “inappropriate statements or propaganda” according to the causes of the storm. The best response strategies to all kinds are described in the text. In addition, when used more response strategies, Online Firestorm duration may longer. There are many factors affecting the Online Firestorm, after the discussion and analysis found that "negative information dissemination platform", "the using of response strategies" and "the scale and nature of the enterprises" and as the factors that most likely to affect the Online Firestorm.