<span style="">四川九寨沟7.0级地震微博灾情信息特征分析</span>-华南地震

文章信息/Info

Title:: Characteristic Analysis on Disaster Information on Microblog about Jiuzhaigou M 7.0 Earthquake in Sichuan Province

Author(s):: MAO Zhenjiang; LYU Jiali; CAO Yanbo; ZHENG Chuan; Yunnan Earthquake Agency，Kunming 650224，China

Keywords:: Jiuzhaigou Earthquake; Microblog; Data acquisition; Data analysis; Disaster analysis

摘要:: 通过调用新浪微博官方API的方式，获取了四川九寨沟7.0级地震震后微博信息，对获取到的数据进行了分类统计、微博词频统计与时空特征分析。统计分析结果表明：在分类统计方面，地震发生之后24 h内，与地震相关微博中人的反应占比达到73%，救援行动占比达到11%，这时由于微博本身特点以及民众对救援的期望造成的。在词频统计方面，高频名词表明震后24 h内微博上的热点事件，而高频动词与形容词表明民众会在震后变得焦虑和不安并通过在网上互相激励来缓解震后的不安和焦虑。时间特征表明震后0～4 h内，有大量和地震相关的灾情信息会通过微博博文内容的方式发布，而随着应急救援行动的进行，在震后12 h以后，民众的情绪会逐渐平复，社会及民众的关注度也随之降低。空间特征表明，由于震后通信中断与网络堵塞，微博灾情基本成点状分布，随后随着通信与网络的恢复、应急救援的进行微博灾情逐渐变为带状分布并进而趋向于形成一个面。

Abstract:: By invoking the official API of Sina Microblog，the post-earthquake information on microblog about Jiuzhaigou M 7.0 Earthquake in Sichuan Province is obtained，and the data are classified in types and word frequency，and analyzed by temporal and spatial characteristics. Statistical analysis shows that within 24 hours after the earthquake，73% of the respondents responded to the earthquake and 11% to the rescue operations. This is due to the characteristics of the microblog itself and people’s expectations for rescue. On the aspect of word-frequency statistics，high-frequency nouns indicate hot events on microblogs within 24 hours after the earthquake，while high-frequency verbs and adjectives indicate that people will become anxious and uneasy after the earthquake and would alleviate the anxiety by stimulating each other online.