網友的互動型態，為描述訊息如何在網友間傳遞的網絡，不僅保留口碑數量的訊息，還能從互動型態的結構中觀察出網友如何互動，是一個能展現社群內部真正活動樣貌的方法。本文目的在於訂定一個衡量互動型態的方法，並探討其與銷售量之間的關聯。實際作法為利用 Mobile01 上2016年台灣的前60大暢銷車款的網路口碑，以每款車為主題繪製網友的互動網絡，並探討互動型態中隱含的訊息，與銷售量之間的關聯。主要貢獻為利用社群網路分析的指標，衡量此網路結構，並發現在不同的網絡大小下，互動網絡結構與銷售量間存在著不同的影響。

Interact network of netizens is a good way to describe social community status. It not only keeps the number of word-of-mouth, but also shows how netizens interact each other. The purpose of this article is to develop a methodology for measuring this kind of network and to explore its relationship with sales. The thesis is that using the eWOM data of top 60 sales car on Mobile01 forum with crawler technique for building internet users’ interact network. The main contribution is to take advantage of the indicators of social network analysis to measure this network structure and find that network sizes moderates the relationship between interact network’s structure and sales.

第一章 緒論....................................................................................................................... 1
第一節 研究背景............................................................................................... 1
第二節 研究動機............................................................................................... 1
第三節 研究目的............................................................................................... 2
第二章 文獻探討............................................................................................................... 2
第一節 反應....................................................................................................... 3
第二節 網路口碑............................................................................................... 4
第三節 傳遞者................................................................................................... 4
第四節 網路結構............................................................................................... 5
第三節 研究方法 ........................................................................................................... 10
第一節 資料搜集與方法................................................................................. 10
第二節 互動網絡建立…................................................................................. 14
第三節互動網絡的隱含的訊息........................................................................15
第四節 研究議題與分析流程......................................................................... 16
第四節 分析結果..............................................................,,,............................................19
第一節 不同大小網路的結構差異.................................................................. 19
第二節 不同大小網路的成員組成差異............................................................21
第三節 討論族群的差異....................................................................................22
第四節不同族群的網絡結構與銷售量的關聯..................................................24
第五節 結論與建議......................................................................................................... 27
第六節 研究限制與未來研究方向................................................................................. 27
第七節 參考文獻............................................................................................................. 28
附錄 車款口碑資料關鍵字..........................................................................................32

Ajzen, I., (1991) The theory of planned behaviour, Organisational Behaviour and Human Decision Processes 50,179–211.

Amblee, N., & Bui, T. (2007). Freeware downloads: An empirical investigation into the impact of expert and user reviews on demand for digital goods. In Proceedings of the 13th Americas Conference on Information Systems, Keystone, Colorado.

Arenas-Márquez, F., Martínez-Torres, M. and Toral, S. (2014). Electronic word-of-mouth communities from the perspective of social network analysis. Technology Analysis & Strategic Management, 26(8), pp.927-942.

Buttle, F. A. (1998). Word of mouth: Understanding and managing referral marketing. Journal of Strategic Marketing, 6(3), 241–254.

Bhattacherjee, A., Sanford, C. (2006). Influence processes for information technology acceptance: an Elaboration Likelihood Model, MIS Quarterly 30 (4)

Bronner, F. & de Hoog, R. (2010). Vacationers and eWOM: Who Posts, and Why, Where, and What?. Journal of Travel Research, 50(1), pp.15-26.

Chen, P. Y., Wu, S. Y., & Yoon, J. (2004). The impact of online recommendations and consumer feedback on sales. In Proceedings of the 25th Annual International Conference on Information Systems (pp.711–724), Washington, DC., USA.

Chen, Y., Tang, K., Wu, C. and Jheng, R. (2014). Predicting the influence of users’ posted information for eWOM advertising in social networks. Electronic Commerce Research and Applications, 13(6), pp.431-439.

Cheung, C.M.K., Lee, M.K.O. (2012) What drives consumers to spread electronic word of 641 mouth on online consumer-opinion platform, Decision Support Systems 53 (1) 218–225.

Cheung, C. and Thadani, D. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), pp.461-470.

Cheung, C. and Thadani, D. (2012). The impact of electronic word-of-mouth communication: A literature analysis and integrative model. Decision Support Systems, 54(1), pp.461-470.

Chang, M.K., Cheung, W., Lai, V.S. (2005). Literature derived reference models for the adoption of online shopping, Information Management 42 543–559.

Cheung, C.M.K., Lee, M.K.O., Rabjohn, N. (2008).The impact of electronic word-of-mouth: the adoption of online opinions in online customer communities, Internet Re- search 18 (3) 229–247.

Chen, Y., and Xie, J. (2005). Online consumer review: A new element of marketing communications mix. Working Paper, the 2nd Winter Product & Service Innovation Conference, Utah.

Chevalier, J. A., & Mayzlin, D. (2006). The effect of word of mouth on sales: Online book reviews. Journal of Marketing Research, 43(3), 345–354.

Chen. (2005). 網路學習社群中的潛水現象:一種被忽略的充分參與

Duan, W., Gu, B., & Whinston, A. B. (2008). The dynamics of online word-of-mouth and product sales An empirical investigation of the movie industry. Journal of Retailing, 84(2), 233 242.

Davis, A., and Khazanchi, D. (2008). An empirical study of online word of mouth as a predictor for multi-product category e-commerce sales. Electronic Markets, 18(2), 130 141.

Dellarocas, C. (2003) The digitization of word of mouth: promise and challenges of online feedback mechanisms, Management Science 49 (10) 1407–1424.

Freeman, L. C. (1979). Centrality in social networks conceptual clarification.
Social Networks, 1(3), 215-239.

Godes, D. and Mayzlin, D. (2004). Using Online Conversations to Study Word-of-Mouth Communication. Marketing Science, 23(4), pp.545-560.

Harvard business review on reinventing your marketing. (2011). Boston, Mass.: Harvard Business Review Press.

Hennig-Thurau, T. and Walsh, G. (2003) Electronic word-of-mouth: Motives for and consequences of reading customer articulations on the internet. Int. J. Electron. Commer. 2003, 8, 51–74. 

Hovland, C.L., (1948). Social communication, Proceedings of the American Philosophical Society 92 (5) 371–375.

He, S. and Bond, S. (2015). Why Is the Crowd Divided? Attribution for Dispersion in Online Word of Mouth. Journal of Consumer Research, 41(6), pp.1509-1527.

Kamins, M.A. & Assael, H. (1987).Two-sided versus one-sided appeals: a cognitive perspec- tive on argumentation, source derogation, and the effect of disconfirming trial on belief change. Journal of Marketing Research 24, 29–39.

Keller, E. and Berry, J. (2003).The Influentials, Free Press.

Li, X., & Hitt, L. M. (2008). Self-selection and information role of online product
reviews. Information Systems Research, 19(4), 456 474.

Liu, Y. (2006). Word of mouth for movies: Its dynamics and impact on box office revenue. Journal of Marketing, 70(3), 74 89.

Liang, T., Li, X., Yang, C. and Wang, M. (2015). What in Consumer Reviews Affects the Sales of Mobile Apps: A Multifacet Sentiment Analysis Approach. International Journal of Electronic Commerce, 20(2), pp.236-260.

Liu, R. and Zhang, W. (2010) Informational influence of online customer feedback: an empirical study, Database Marketing & Customer Strategy Management 17 (2)
120–131.

Leshed, G. (2005). Posters, lurkers, and in between: A multidimensional model of
online community participation patterns. Poster presented at HCI
International, Las Vegas, NV.

Marin, A., Wellman, B., Scott, P. J. P., & Carrington, P. P. (2011). Social network
analysis: An introduction. Scott J, Carrington PJ, editors. The SAGE
Handbook of Social Network Analysis, 11-25.

Newman, M.E.J. (2003). The structure and function of complex networks. SIAM Review 45, no. 2: 167–256.

Park, D. and Lee, J. (2008). eWOM overload and its effect on consumer behavioral intention depending on consumer involvement, Electronic Commerce Research and Applications 7 (4) 386–398.

Reingen, P. H., Foster, B. L., Brown, J. J., & Seidman, S. B. (1984). Brand congruence in interpersonal relations: A social network analysis. Journal of Consumer Research, 11(3), 771 783.

Zhu, F. & Zhang, X. (2006). The influence of online consumer reviews on the demand for experience goods: The case of video games’. 27th International Conference on Information Systems (ICIS-27), Milwaukee, WI.