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Hoanh Su Le,Cuong Trieu,Thanh Ho,Jong-Hwa Lee,Hyun-Kyu Lee 한국인터넷전자상거래학회 2017 인터넷전자상거래연구 Vol.17 No.5
The increasing of users in social networking services in Vietnam help companies have better communication channels with customers. Nowadays, any companies can easily invest tools and human to monitor and harvest customer-generated contents not only about their own brands but also about their competitive brands on social media sites. In order utilize the value in the harvested data, certain analytic techniques are required. This paper proposed a method to apply mining social media data in the context of fastfood brands. We collected data from top fastfood chains including Lotteria, MacDonald, KFC, Vietnam Pizza Hut and Pepperonis Vietnam and applied machine learning to classify the sentiment of informal text data. The results show that applying neural network machine learning in sentiment analytics of social media text data is suitable for sentiment analytics and applicable for future data prediction in fastfood industry.