论文标题
基于文本挖掘和社交媒体分析的地震影响分析
Earthquake Impact Analysis Based on Text Mining and Social Media Analytics
论文作者
论文摘要
地震对广泛地区产生了深远的影响，紧急救援行动可能会受益于有关灾难范围和程度的社交媒体信息。因此，这项工作提出了一种基于文本挖掘的方法，以收集和分析社交媒体数据以进行早期地震影响分析。首先，基于Crawler Technology的SINA微博收集了灾难性的微博收集。然后，在数据清洁数据后，进行了一系列分析，包括（1）热词分析，（2）微博的数量趋势，（3）公众意见情绪的趋势，以及（4）地震影响分析的基于关键字和基于规则的文本分类。最后，分析了最近在中国具有相同大小和焦点深度的两次地震，以比较其影响。结果表明，公众舆论趋势分析和舆论情绪的趋势可以在早期估计地震的社会影响，这将有助于决策和救援管理。
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.
