Progress in Computing Applications Asgarali Bouyer 7 2 2018 https://doi.org/10.6025/pca/2018/7/2/47-55 http://www.dline.info/pca/fulltext/v7n2/pcav7n2_1.pdf With the rapid development of computers, internet, social media and networks, and other digital multimedia technologies, it is needed to use a mechanism that can predict the needs and desires of users and recommend the bests for them. Introducing the social networks’ information into the traditional collaborative filtering (CF) algorithm, the essay studies the changes of user preference in social networks. Recently a lot of research efforts have been spent on building recommender systems by utilizing the abundant online social network’s data. This paper proposes an improved collaborative filtering algorithm based on fuzzy logic and Social Network Information. The proposed method enhances the accuracy of recommendations by combining the social tags, fuzzy logic and social networks’ information such as friendship and groups’ membership. Through the experiment, the improved algorithm has higher accuracy than the traditional filtering algorithms in the top-N recommendation list. It proves that the social networks’ information of users can affect the user’s preference.