Personal preferences analysis of user interaction based on social networks

Under the current situation the booming social networks, users interact between people with the way of social networks platforms (such as: press like, join fans pages and groups), and for these interactive information on social platform can fully represent that oneself is interested in the content of information sources in different social group. Therefore, how to collect user behavior patterns (Users Behavior) generated by social interaction, and then analyze and understand user preferences by these interactive data would be the purpose to discuss and to do the research of the paper. Furthermore, for many brand enterprises, 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 paper, mainly expectations for analysis by the data of user's personal interaction on the social network, such as: user clicked fan page, user press like article, user share data 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 paper at last through the actual business verification, the research can improve website browsing pages growth 8%, site bounce rate dropped 11%, commodities click through rate growth 36%, more fully represents the results of this research fit the use's preference.