IJERPH, Vol. 18, Pages 8000: Microblog Topic-Words Detection Model for Earthquake Emergency Responses Based on Information Classification Hierarchy

IJERPH, Vol. 18, Pages 8000: Microblog Topic-Words Detection Model for Earthquake Emergency Responses Based on Information Classification Hierarchy International Journal of Environmental Research and Public Health doi: 10.3390/ijerph18158000 Authors: Su Ma Qiu Shi Zhang Chen 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 the topic-words detection model are verified using 2201 messages obtained after the 2014 Ludian earthquake. The results show that the information acquisition time of the model is short. The validity of the whole set is 96.96%, and the average and maximum validity of single words are 78% and 100%, respectively. In the Ludian and Jiuzhaigou earthquake cases, new topic-words added to different earthquakes only reach single digits in vali...
Source: International Journal of Environmental Research and Public Health - Category: Environmental Health Authors: Tags: Article Source Type: research