Exploring the Requirements of Pandemic Awareness Systems: A Case Study of COVID-19 Using Social Media Data

Esmaeil Shakeri, B. Far
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引用次数: 2

Abstract

With the exponential growth of social media platforms like Twitter, a seemingly vast amount of data has become available for mining to draw conclusions about various topics, including awareness systems requirements. The exchange of health-related information on social media has been heralded as a new way to explore information-seeking behaviour during pandemics and design and develop awareness systems that address the public's information needs. Online datasets such as Twitter, Google Trends and Reddit have several advantages over traditional data sources, including real-time data availability, ease of access, and reduced cost. In this paper, to explore the pandemic awareness systems (PAS), requirements, we utilize data from the large accessible database of tweets and Reddit's posts to explore the contextual patterns and temporal trends in Canadians' information-seeking behaviour during the COVID-19 pandemic. To validate our inferences and to understand how Google searches regarding COVID-19 were distributed throughout the course of the pandemic in Canada, we complement our Twitter and Reddit data with that collected through Google Trends, which tracks the popularity of specific search terms on Google. Our results show that Social media content contains useful technical information and can be used as a source to explore the requirements of pandemic awareness systems.
探索大流行意识系统的要求:以COVID-19为例,使用社交媒体数据
随着Twitter等社交媒体平台的指数级增长,似乎有大量的数据可供挖掘,以得出关于各种主题的结论,包括感知系统需求。在社交媒体上交流与健康有关的信息被认为是探索大流行期间寻求信息行为以及设计和开发满足公众信息需求的认识系统的一种新方法。与传统数据源相比,Twitter、Google Trends和Reddit等在线数据集有几个优势,包括实时数据可用性、易于访问和降低成本。在本文中,为了探索大流行意识系统(PAS)的要求,我们利用来自twitter和Reddit的大型可访问数据库的数据,探索加拿大人在COVID-19大流行期间寻求信息行为的上下文模式和时间趋势。为了验证我们的推断,并了解在加拿大大流行期间,关于COVID-19的谷歌搜索是如何分布的,我们用谷歌趋势收集的数据补充了Twitter和Reddit的数据,谷歌趋势追踪了谷歌上特定搜索词的受欢迎程度。我们的研究结果表明,社交媒体内容包含有用的技术信息,可以作为探索大流行意识系统要求的来源。
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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