We develop a recommendation system for news movies that can reflect social trends as well as personal Preferences. Many news movies are delivered every day due to the development of information and communications technology, and the audiences may be suffering from finding proper news movies among them. In order to support audiences, we develop a topicality measure for social trends, as well as that of personal preferences, and find them successful in recommendation.