| Summary: | 碩士 === 中國文化大學 === 資訊管理學系 === 103 === As the popularity of Internet access grows, Internet has become an essential in their daily life for people who rely on it. More and more community network provides a new way to exchanging and sharing information. The community network platform provides product information and functions that make consumer to get the greatest satisfaction, or to find out consumers interests and highly related products. Since the advent of the Internet community, many business owners and advertisers have been researching to understand consumer needs and preferences for products of interest.
In this research, we use Decision tree C4.5 and CART for consumers to identify the key attributes of social media features that highly affect the response rate of users to web advertising. Finally, the advertising forecasting models are build for each user using two techniques: Decision tree and Logistic regression. Experimental results show that Logistic regression outperforms Decision tree.
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