Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text
With the rapid development of Internet information technology, the advantages of social media in terms of speed, content, form, and effect of communication are becoming increasingly significant. In recent years, more and more researchers have paid attention to the special value and role of social me...
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| Format: | Article |
| Language: | English |
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Graz University of Technology
2021-02-01
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| Series: | Journal of Universal Computer Science |
| Subjects: | |
| Online Access: | https://lib.jucs.org/article/65106/download/pdf/ |
| _version_ | 1830353299595853824 |
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| author | Hua Bai Hualong Yu Guang Yu Alvaro Rocha Xing Huang |
| author_facet | Hua Bai Hualong Yu Guang Yu Alvaro Rocha Xing Huang |
| author_sort | Hua Bai |
| collection | DOAJ |
| description | With the rapid development of Internet information technology, the advantages of social media in terms of speed, content, form, and effect of communication are becoming increasingly significant. In recent years, more and more researchers have paid attention to the special value and role of social media tools in disaster information emergency management. Weibo is the most widely used Chinese social media tool. To effectively mine and apply the emergency function of disaster situation microblogs, a disaster situation information discovery and collection system capable of online incremental identification and collection are constructed for massive and disordered disaster microblog text streams. First, based on the deep learning- trained word vector model and a large-scale corpus, an unsupervised short-text feature representation method of disaster situation Weibo information is developed. According to the experimental results of the feature combination test and the training set scale test, the SVM algorithm was selected for disaster microblog information classification, which realized effective identification of disaster situation micro-bloggings. Then, the temporal information similarity and geographic information similarity are used to improve the single text similarity algorithm, and a Chinese disaster event online real-time detection model is constructed. Furthermore, the disaster-affected areas can be achieved in real-time based on the detection results. By crawling and classifying the micro-bloggings from the disaster-affected areas, it is possible to realize the incremental identification and collection of online disaster situation Weibo information. Finally, the empirical analysis of disaster events such as the “Leshan Earthquake” shows that the real- time intelligent identification and collection system for disaster situation Weibo micro-bloggings developed in this paper can obtain large-scale and useful data for disaster emergency management, which proving that this system is effective and efficient. |
| first_indexed | 2024-12-20T01:11:21Z |
| format | Article |
| id | doaj.art-698de72ba28343c091fbf61f95b2ed09 |
| institution | Directory Open Access Journal |
| issn | 0948-6968 |
| language | English |
| last_indexed | 2024-12-20T01:11:21Z |
| publishDate | 2021-02-01 |
| publisher | Graz University of Technology |
| record_format | Article |
| series | Journal of Universal Computer Science |
| spelling | doaj.art-698de72ba28343c091fbf61f95b2ed092022-12-21T19:58:41ZengGraz University of TechnologyJournal of Universal Computer Science0948-69682021-02-0127223025210.3897/jucs.6510665106Analysis on an Auto Increment Detection System of Chinese Disaster Weibo TextHua Bai0Hualong Yu1Guang Yu2Alvaro Rocha3Xing Huang4Fujian Normal UniversityHarbin Institute of TechnologyHarbin Institute of TechnologyISEG, University of LisbonSouthwest University of Science and TechnologyWith the rapid development of Internet information technology, the advantages of social media in terms of speed, content, form, and effect of communication are becoming increasingly significant. In recent years, more and more researchers have paid attention to the special value and role of social media tools in disaster information emergency management. Weibo is the most widely used Chinese social media tool. To effectively mine and apply the emergency function of disaster situation microblogs, a disaster situation information discovery and collection system capable of online incremental identification and collection are constructed for massive and disordered disaster microblog text streams. First, based on the deep learning- trained word vector model and a large-scale corpus, an unsupervised short-text feature representation method of disaster situation Weibo information is developed. According to the experimental results of the feature combination test and the training set scale test, the SVM algorithm was selected for disaster microblog information classification, which realized effective identification of disaster situation micro-bloggings. Then, the temporal information similarity and geographic information similarity are used to improve the single text similarity algorithm, and a Chinese disaster event online real-time detection model is constructed. Furthermore, the disaster-affected areas can be achieved in real-time based on the detection results. By crawling and classifying the micro-bloggings from the disaster-affected areas, it is possible to realize the incremental identification and collection of online disaster situation Weibo information. Finally, the empirical analysis of disaster events such as the “Leshan Earthquake” shows that the real- time intelligent identification and collection system for disaster situation Weibo micro-bloggings developed in this paper can obtain large-scale and useful data for disaster emergency management, which proving that this system is effective and efficient.https://lib.jucs.org/article/65106/download/pdf/Social mediaDisastersEmergency managementWor |
| spellingShingle | Hua Bai Hualong Yu Guang Yu Alvaro Rocha Xing Huang Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text Journal of Universal Computer Science Social media Disasters Emergency management Wor |
| title | Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text |
| title_full | Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text |
| title_fullStr | Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text |
| title_full_unstemmed | Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text |
| title_short | Analysis on an Auto Increment Detection System of Chinese Disaster Weibo Text |
| title_sort | analysis on an auto increment detection system of chinese disaster weibo text |
| topic | Social media Disasters Emergency management Wor |
| url | https://lib.jucs.org/article/65106/download/pdf/ |
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