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在中国COVID-19流行病的不同阶段,对微博上寻求帮助的信息进行了多维比较研究

Jianhong Jiang¹, Chenyan Yao¹, Xinyi Song¹

¹School of Business, Guilin University of Electronic Technology, Guilin, Guangxi, China.

Frontiers in public health

|February 29, 2024

概括

在微博上寻求帮助的COVID-19随着时间的推移而演变. 内容重点转移,消息的病毒性与早期的案例数相关,受媒体类型和文本长度的影响.

科学领域:

社会科学社会科学社会科学
计算机科学计算机科学
公共卫生公共卫生

背景情况:

在COVID-19大流行期间,像微博这样的社交媒体平台对于寻求实际问题的个人来说变得至关重要.
鉴于病毒,政策和公众观念的变化,了解这些寻求帮助行为的演变至关重要.

研究的目的:

分析COVID-19流行病不同阶段在微博上寻求帮助信息的变化.
调查内容类别的转移,时间分布模式,以及影响消息转发的因素.

主要方法:

利用CNN和xlm-roberta-large模型对微博寻求帮助的消息进行文字分类.
采用TLCC算法来研究时间分布和计算时间滞后.
应用负二项式回归来分析转发推特的影响因素.

主要成果:

在不同流行病阶段,寻求帮助的内容重点在不同阶段有很大的不同.
在中期寻求帮助的新信息和确诊的COVID-19病例之间观察到16天的时间延迟,但在后期没有.
包括图像/视频和更长的文本长度在所有阶段都对转发量产生了积极的影响.

结论:

在Weibo上寻求帮助的行为在整个COVID-19大流行期间动态演变.
调查结果为决策者,寻求帮助者和未来关于在健康危机期间在线社交行为的研究提供了有价值的见解.

关键词:

在 COVID-19 疫情中,数据挖掘是数据挖掘的一个方法.寻求帮助的行为.神经网络的神经网络的神经网络回归分析是一种回归分析.社交媒体社交媒体

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