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With the development of e-commerce, many products are now being soldworldwide, and manufacturers are eager to obtain a better understanding ofcustomer behavior in various regions. To achieve this goal, most previousefforts have focused mainly on questionnaires, which are time-consuming andcostly. The tremendous volume of product reviews on e-commerce websites hasseen a new trend emerge, whereby manufacturers attempt to understand userpreferences by analyzing online reviews. Following this trend, this paperaddresses the problem of studying customer behavior by exploiting recentlydeveloped opinion mining techniques. This work is novel for three reasons.First, questionnaire-based investigation is automatically enabled by employingalgorithms for template-based question generation and opinion mining-basedanswer extraction. Using this system, manufacturers are able to obtain reportsof customer behavior featuring a much larger sample size, more directinformation, a higher degree of automation, and a lower cost. Second,international customer behavior study is made easier by integrating tools formultilingual opinion mining. Third, this is the first time an automaticquestionnaire investigation has been conducted to compare customer behavior inChina and America, where product reviews are written and read in Chinese andEnglish, respectively. Our study on digital cameras, smartphones, and tabletcomputers yields three findings. First, Chinese customers follow the Doctrineof the Mean, and often use euphemistic expressions, while American customersexpress their opinions more directly. Second, Chinese customers care more aboutgeneral feelings, while American customers pay more attention to productdetails. Third, Chinese customers focus on external features, while Americancustomers care more about the internal features of products.

Online shopping behavior study based on multi-granularity opinion mining: China vs. America