The prosperity of computer-mediated communication booms customers’ online communication, known as the electronic word-of-mouth (eWOM). Although the importance of eWOM in viral marketing and consumer decision making has been widely accepted, existing research mainly focused on the motivation and effects of different eWOM behaviours, while research on eWOM diffusion is still limited. As social networking site has become a popular medium for eWOM, this study will focus on social networking sites, aiming to examine the patterns of eWOM diffusion and the features that shape those diffusion patterns, especially the effects of content emotions. Using data extracted from Twitter and Weibo Microblogging, we will apply sentiment analysis, social network analysis and machine learning techniques to test our conceptual model of eWOM diffusion and its predictive power.

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