Design and Implementation of Facebook Crawler Based on Interaction Simulation

The extensive use of Online Social Networks (OSNs) has attracted such wide attention of academia that OSNs have become a hot topic. Based on the interaction simulation, we have designed and implemented a Facebook crawler, which can obtain the complete friend list of a Facebook user and overcome the drawback in [7] that the crawler can get at most 400 friends. We make an analysis and visualization of the crawled dataset, and find that 36.5% of Facebook users have changed the default privacy setting, compared to 26.6% and 16% in [7, 20] respectively, implying that the awareness of privacy protection of Facebook users has been greatly improved.