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This paper demonstrates a system that exploits graph mining, social network analysis, and agent-based crowd simulation techniques to investigate the evacuation dynamics during fire emergency. We create a novel evacuation planning system, EvaPlanner, to deal with three tasks. First, the system identifies the preferable locations to establish the exits to facilitate efficient evacuation from the dangerous areas. Second, it determines the most effective positions to place the emergency signs such that panic crowd can quickly find the exits. Third, it faithfully simulates the evacuation dynamics of crowd considering not only the individual movement kinetics but also the social connections between people. EvaPlanner provides a flexible experimental platform for investigating the evacuation dynamics under a variety of settings, and can further be utilized for animation and movie production. In addition, it can serve as a tool to assist architects address the safety concern during the planning phase. The demo system can be found in the link: http://mslab.csie.ntu.edu.tw/evaplanner/