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In the age of information network explosion, users can be connected to various forms of social networking sites whenever and wherever through the Internet, And through the social networking platform to interact with people. Through the media in this way, people know each other's interests and preferences by the relationship between social friends, but for many international companies, it is important to know how to understand individual preferences, because when you know the individual preference information, it can carry out personal preference for advertising, product recommendation, article recommended and other diversified personal social service, which can increase the click rate and exposure of the products, better close to the needs of the user's life. Therefore, with the above through social science and technology development trend arising from current social phenomenon, research of this thesis, mainly expectations for analysis by the information of interaction between people on the social network, such as: user clicked fan page, user's graffiti wall message information, friend clicked fan page etc. three kinds of personal information for personal preference analysis, and from this huge amount of personal data to find out corresponding diverse group for personal preference category. We can by personal preference information for diversify personal advertising, product recommendation and other services. The thesis at last through the actual business verification, the research can improve website browsing pages growth 11%, time on site growth 15%, site bounce rate dropped 13.8%, product click through rate growth 43%, more fully represents the results of this research fit the use's preference.

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