  With the development of e-commerce, many products are now being sold
worldwide, and manufacturers are eager to obtain a better understanding of
customer behavior in various regions. To achieve this goal, most previous
efforts have focused mainly on questionnaires, which are time-consuming and
costly. The tremendous volume of product reviews on e-commerce websites has
seen a new trend emerge, whereby manufacturers attempt to understand user
preferences by analyzing online reviews. Following this trend, this paper
addresses the problem of studying customer behavior by exploiting recently
developed opinion mining techniques. This work is novel for three reasons.
First, questionnaire-based investigation is automatically enabled by employing
algorithms for template-based question generation and opinion mining-based
answer extraction. Using this system, manufacturers are able to obtain reports
of customer behavior featuring a much larger sample size, more direct
information, a higher degree of automation, and a lower cost. Second,
international customer behavior study is made easier by integrating tools for
multilingual opinion mining. Third, this is the first time an automatic
questionnaire investigation has been conducted to compare customer behavior in
China and America, where product reviews are written and read in Chinese and
English, respectively. Our study on digital cameras, smartphones, and tablet
computers yields three findings. First, Chinese customers follow the Doctrine
of the Mean, and often use euphemistic expressions, while American customers
express their opinions more directly. Second, Chinese customers care more about
general feelings, while American customers pay more attention to product
details. Third, Chinese customers focus on external features, while American
customers care more about the internal features of products.
