Microblog Topic-Words Detection Model for Earthquake Emergency Responses Based on Information Classification Hierarchy

Xiaohui Su, Shurui Ma, Xiaokang Qiu, Jiabin Shi, Xiaodong Zhang and Feixiang Chen
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Xiaohui Su: School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
Shurui Ma: School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
Xiaokang Qiu: School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
Jiabin Shi: School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
Xiaodong Zhang: College of Land Science and Technology, China Agricultural University, Beijing 100083, China
Feixiang Chen: School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China

IJERPH, 2021, vol. 18, issue 15, 1-20

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 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 validity. Therefore, the experiments show that the proposed model can quickly obtain effective and pertinent information after an earthquake, and the complete performance of the earthquake emergency information classification hierarchy can meet the needs of other earthquake emergencies.

Keywords: earthquake emergency; effectiveness of topic-word; information classification; microblog; topic-words detection (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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