In this paper, researchers investigated current fashion brands’ social media micro-blogging marketing strategy and consumers’ word of mouth reactions. More than 5,000 of the micro-blogs posted by fashion brands and 143,000 of customers’ comments were analysed in this study. Researchers firstly investigated the overall micro-blogging marketing structure for each fashion brand and compared them. Then researchers identified the type of expression pattern of each fashion brand currently in the micro-blogging context, negative or positive sentiments. Researchers found that fashion brands are using different micro-blogging marketing strategies. Forever21 used 61% micro-blogs for customer communication. H&M posted very diverse micro-blogs content to their official account. Their main micro-blogs were used for new product promotion (43%) and brand’s live event broadcasting (33%). Luxury brands, such as Burberry, more than 52% of micro-blogs posted last year were used for new product promotion and 36% of their micro-blogs contents included celebrities’ images of wearing Burberry product. Chanel used 60% of their micro-blogs to broadcast and introduce their brand events. There was no sale information posted on Chanel and Burberry’s micro-blogs account. Through sentiment analysis, researchers also found the brands have very positive electronic word of mouth (e-WOM). Particular, luxury fashion brands are having better e-WOM than fast fashion brands.

Within last 10 years, internet has become a daily activity, and humankind had to face the Data Deluge, a dramatic increase of digital data (Economist 2012). Due to exponential increase in amount of digital data, large scale data has become a big issue and hence the term 'big data' appeared. There is no official agreement in quantitative and detailed definition of the 'big data', but the meaning is expanding to its value and efficacy. Big data not only has the standardized personal information (internal) like customer information, but also has complex data of external, atypical, social, and real time data. Big data's technology has the concept that covers wide range technology, including 'data achievement, save/manage, analysis, and application'. To define the connected technology of 'big data', there are Big Table, Cassandra, Hadoop, MapReduce, Hbase, and NoSQL, and for the sub-techniques, Text Mining, Opinion Mining, Social Network Analysis, Cluster Analysis are gaining attention. The three features that 'bid data' needs to have is about creating large amounts of individual elements (high-resolution) to variety of high-frequency data. Big data has three defining features of volume, variety, and velocity, which is called the '3V'. There is increase in complexity as the 4th feature, and as all 4features are satisfied, it becomes more suitable to a 'big data'. In this study, we have looked at various reasons why companies need to impose 'big data', ways of application, and advanced cases of domestic and foreign applications. To correspond effectively to 'big data' revolution, paradigm shift in areas of data production, distribution, and consumption is needed, and insight of unfolding and preparing future business by considering the unpredictable market of technology, industry environment, and flow of social demand is desperately needed.