Social Network Analysis (SNA) is a field of study that focuses on analyzing user profiles and participation on social network channels in order to model relationships between people and to predict certain behaviors or knowledge. To achieve their goals, researchers, interested in SNA, have to extract content and structure from the numerous social networks available today. Existing tools, which help in this task, often require substantial pre-processing or good programming skills which may not be available for all SNA researchers. This paper describes RUM, a data extraction tool which allows researchers to easily extract several types of content and structure that are available on Facebook pages. Consequently, the extracted data can be saved and analyzed. RUM Extractor is easy to set up and use, and it gives flexible options to users to specify the type and amount of content and structure they want to retrieve. The paper also demonstrates how RUM can be exploited by collecting and further analyzing data collected from two popular Arabic news pages.