挖掘社交媒体数据探究自然灾害时公众注意力的变化

Mining social media data to explore shifts in public attention during natural disasters

随着互联网行业的发展,在灾难发生期间,社交媒体已经成为公众重要的交流手段,通过对受灾地区公众的社交媒体数据进行合理的抽取与内容分析,可以为应急管理人员提供有效的决策支持。本研究选取了2021年10月山西暴雨期间的微博数据作为研究数据,通过运用词频-逆文档频率算法(TF-IDF)、中文词法分析(LAC)和百度AI(Artificial Intelligence)情感分析等方法对社交媒体数据进行综合分析以获取该灾害下公众情感以及公众注意力焦点变化趋势,为新媒体时代救援减灾工作提供支撑。

With the development of the Internet industry,during disasters,social media has become an important means of communication for the public.Through reasonable extraction and content analysis of the social media data of the public in the disaster-stricken areas,effective decision-making support can be provided for emergency managers.This study selected the microblog data during the heavy rain in Shanxi in October 2021 as the research data.By using term frequency-inverse document frequency(TF-IDF),with lexical analysis of Chinese(LAC),Baidu artificial intelligence(AI)sentiment analysis and other methods,a comprehensive analysis of social media data were constructed to obtain public sentiment and the changing trend of public attention under the disaster,which provided support for rescue and disaster reduction work in the new media era.