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In recent years, social networking sites have becoming important platforms for users to establish the relationships between each other. As time goes by, the links between people will form the so-called "Strong Links". For those users, information provided by the friends with strong link is considered as more interesting and useful. Most of recent search engines are designed based on only measuring the similarity between keywords and articles. However, the social relations between authors of articles and searcher have not been taken into account in recent research. Therefore, in order to improve the performance of recent search engines, we include the measurement of social relationships in search engine and expect the search quality can be improved. In this study, we collected the data from Facebook to calculate the social relationship. About the content, the data will be processed by using CKIP (Chinese word net) and TF-IDF. Finally, we combine key-word frequency and social relations as a value, which is called the Social Ranking vaule. The value will be used as the key to rank the search results. In this paper, we will also demonstrate a real example to explain the proposed methodology as well as a system interface.