Earthquake Impact Analysis Based on Text Mining and Social Media Analytics
22nd International Conference on Construction Applications of Virtual Reality (CONVR2022), 2022
引用方式: Zheng, Z., Shi, H.Z., Zhou, Y.C., Lu, X.Z., Lin, J.R.* (2022). Earthquake Impact Analysis Based on Text Mining and Social Media Analytics. 22nd International Conference on Construction Applications of Virtual Reality (CONVR2022), 1116-1124. Seoul, South Korea. https://doi.org/10.48550/arXiv.2212.06765
摘要
地震灾害的影响范围巨大，社交媒体作为重要的信息发表渠道，如何高效分析其信息对紧急救援行动具有重要意义。因此，本研究提出了一种基于文本挖掘的方法来收集和分析社交媒体数据，以快速进行地震影响分析。首先，研究基于爬虫技术实现新浪微博灾难相关推文的自动获取；然后，结合数据清理引入一系列分析方法，包括(1)热词分析，(2)微博趋势分析，(3)舆情趋势分析，(4)基于关键词和规则的地震影响文本分析等；最后，研究对比了中国最近发生的两次震级和震源深度相同的地震，比较了它们的影响。结果表明，通过舆情趋势分析和情感分析，可以在地震发生初期预估地震的社会影响，为地震的决策和救援管理提供依据。
Earthquakes have a deep impact on wide areas, and emergency rescue operations may benefit from social media information about the scope and extent of the disaster. Therefore, this work presents a text miningbased approach to collect and analyze social media data for early earthquake impact analysis. First, disasterrelated microblogs are collected from the Sina microblog based on crawler technology. Then, after data cleaning a series of analyses are conducted including (1) the hot words analysis, (2) the trend of the number of microblogs, (3) the trend of public opinion sentiment, and (4) a keyword and rule-based text classification for earthquake impact analysis. Finally, two recent earthquakes with the same magnitude and focal depth in China are analyzed to compare their impacts. The results show that the public opinion trend analysis and the trend of public opinion sentiment can estimate the earthquake’s social impact at an early stage, which will be helpful to decision-making and rescue management.
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The authors are grateful for the financial support received from the National Natural Science Foundation of China (No. 72091512, No. 51908323) and the Tencent Foundation through the XPLORER PRIZE.
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