| 基于微博的芦山地震前后宏观异常信息筛选与分析 |
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| 引用本文： | 苏晓慧,张群燕,张晓东,张旭,李林,刘峻明,黄健熙,苏伟.基于微博的芦山地震前后宏观异常信息筛选与分析[J].震灾防御技术,2013,8(4):451-458. |
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| 作者姓名： | 苏晓慧 张群燕 张晓东 张旭 李林 刘峻明 黄健熙 苏伟 |
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| 作者单位： | 中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083;中国农业大学信息与电气工程学院，北京 100083 |
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| 基金项目： | 国家“十二五”科技支撑计划课题（2012BAK19B04-03） |
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| 摘 要： | 地震宏观异常是指地震前后人的感觉能直接察觉到的自然界异常现象,本研究在芦山地震后,针对公众通过微博发布的异常信息进行搜集,提出从真实性、完整性、信誉度和关联度四方面对公众提供的微博宏观异常信息进行筛选的方法,并根据筛选后的信息从时间角度、空间分布等方面进行芦山地震前后宏观异常信息的分析研究.结果表明,芦山地震前后是有宏观异常出现的,公众关注的异常种类主要为动物异常与天气异常;震前发生宏观异常占宏观异常总数的67％,但仅有30％被发布;微博发布的宏观异常信息中,大多位于距离震中较远的成都市,而非震中地区.微博信息可以作为宏观异常信息的一个主要的及时信息来源,有助于发挥群测群防在防震减灾工作中的作用.
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| 关 键 词： | 微博 芦山地震 宏观异常 信息筛选 |
| 收稿时间： | 8/9/2013 12:00:00 AM |
Analysis on Macroscopic Anomalies before and after Lushan MS7.0 Earthquake based on Weibo |
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| Su Xiaohui,Zhang Qunyan,Zhang Xiaodong,Zhang Xu,Li Lin,Liu Junming,Huang Jianxi and Su Wei.Analysis on Macroscopic Anomalies before and after Lushan MS7.0 Earthquake based on Weibo[J].Technology for Earthquake Disaster Prevention,2013,8(4):451-458. |
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| Authors: | Su Xiaohui Zhang Qunyan Zhang Xiaodong Zhang Xu Li Lin Liu Junming Huang Jianxi and Su Wei |
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| Institution: | College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China |
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| Abstract: | There are a lot of abnormal phenomena observed before earthquakes, those which can directly perceived by people are called macroscopic anomalies. In this study we collected abnormal information which were sent by public in Weibo when Lushan earthquake happened. We proposed a filtering method which contains four indexes to screen the information from temporal and space distribution aspects. The indexes include authenticity, credit-worthless, integrity, and relevance. Our results indicate that there are some macroscopic anomalies happened before and after Lushan earthquake, in which anomalies from animal behavior and atmosphere got more attention from the public. Among 67% of the macroscopic anomalies only 30% was sent and published before the earthquake. The anomaly information which sent by Weibo is located in Chengdu which is not within the epicenter area. Weibo information is a major and timely source for macroscopic anomalies, and is helpful to the public which make an important role in earthquake disaster preparedness and reduction. |
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| Keywords: | Weibo Lushan MS7 0 earthquake Macroscopic anomaly Information filtering |
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