International Journal of Environmental Research and Public Health Article Microblog Topic-Words Detection Model for Earthquake Emergency Responses Based on Information Classification Hierarchy Xiaohui Su 1,2 , Shurui Ma 1,2, Xiaokang Qiu 1, Jiabin Shi 1,2, Xiaodong Zhang 3 and Feixiang Chen 1,2,* 1 School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China;
[email protected] (X.S.);
[email protected] (S.M.);
[email protected] (X.Q.);
[email protected] (J.S.) 2 Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China 3 College of Land Science and Technology, China Agricultural University, Beijing 100083, China;
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[email protected] Abstract: Social media data are constantly updated, numerous, and characteristically prominent. To quickly extract the needed information from the data to address earthquake emergencies, a topic-words detection model of earthquake emergency microblog messages is studied. First, a case analysis method is used to analyze microblog information after earthquake events. An earthquake emergency information classification hierarchy is constructed based on public demand. Then, subject sets of different granularities of earthquake emergency information classification are generated through the classification hierarchy. A detection model of new topic-words is studied to improve and perfect the sets of topic-words. Furthermore, the validity, timeliness, and completeness of Citation: Su, X.; Ma, S.; Qiu, X.; Shi, the topic-words detection model are verified using 2201 messages obtained after the 2014 Ludian J.; Zhang, X.; Chen, F. Microblog Topic-Words Detection Model for earthquake.