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Analysis of the publicly available data from social networks may benefit many practical applications, and analysis of text messages to reveal emergent cases is an urgent and important task. Wide spread of social media may be used in order to detect and manage rescue operations. In this paper, an approach to analysis of public messages from social network for understanding the emergency scenario developing and rescue operation managing is proposed. This approach allows filtering data according to the settings chosen by researcher and visualizing the result of analysis using two options: placing number of messages on the map and creating a pie diagram. The designed application was tested on data from VAST Mini-Challenge 3 2019 describing social network response on earthquake. The experiments showed that the proposed approach allows detecting the most dangerous areas in the city and highlighting them visually.