Web media is becoming popular nowadays for people to read news or articles. It is interesting and important for the web media providers to learn the browsing behaviors of their readers and authors. In this paper, we present a visual analytics system for discovering the browsing and authoring behaviors in web media based on users' web page clickstream data. Our system provides multiple views of visualization with user interaction, including a scatter plot providing an overview to help analysts locate data of interest, and a force-directed graph for investigating relations between data entities. Interesting behaviors have been explored and found by using the proposed multiple views system.