Social media-based demographic and sentiment analysis for disaster responses.

Q3 Medicine
Seungil Yum
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引用次数: 0

Abstract

This study explores disaster responses across the United States for Winter Storm Jaxon in 2018 by utilizing demographic and sentiment analysis for Twitter®. This study finds that people show highly fluctuated responses across the study periods and highest natural sentiment, followed by positive sentiment and negative sentiment. Also, some sociodemographic and Twitter variables, such as gender and long text, are strongly related to human sentiment, whereas other sociodemographic and Twitter variables, such as age and the higher number of retweets, are not associated with it. The results show that governments and disaster experts should consider a multitude of sociodemographic and Twitter variables to understand human responses and sentiment during natural disaster events.

基于社交媒体的人口和情感分析,用于灾害应对。
本研究通过对 Twitter® 进行人口和情感分析,探讨美国各地对 2018 年冬季风暴 Jaxon 的灾难反应。本研究发现,人们在研究期间的反应波动很大,自然情绪最高,其次是积极情绪和消极情绪。此外,一些社会人口变量和 Twitter 变量(如性别和长文本)与人类情感密切相关,而其他社会人口变量和 Twitter 变量(如年龄和较高的转发次数)则与之无关。研究结果表明,政府和灾害专家应考虑多种社会人口变量和 Twitter 变量,以了解自然灾害事件中人类的反应和情绪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Emergency Management
Journal of Emergency Management Medicine-Emergency Medicine
CiteScore
1.20
自引率
0.00%
发文量
67
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