How to Meet the Diverse Needs of Consumers: Big Data Mining based on Online Review

Gu, Wei
Hu, Rui
Song, Yanan
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This article applied Word2vec and image mining on OCRs analysis. Data from showed that in Beijing, good taste is the primary factor for customers to choose a restaurant. Unlike the general opinion, careers and locations have little influence on cuisine choice in Beijing. Hot pot is the most popular one all over the city. Warm color, medium dark light and saturation with certain amount of grey are three key aspects for an enjoyable dining environment. Offline mouth to mouth recommendation is the most useful way to spread a restaurants reputation. So making the antecedent consumer satisfy is the most applied way to appeal new ones. This findings can help restaurant owners to run a better business and promote the satisfactory.
Social Media Management in Big Data Era, big data, social media ocrs, consumer preference, dining industry
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