COVID-19: Understanding Construction Industry Responses on Twitter in the Emergence of Novel Coronavirus
COVID-19: Understanding Construction Industry Responses on Twitter in the Emergence of Novel Coronavirus
复制标题
COVID-19：了解新型冠状病毒出现时建筑行业在 Twitter 上的反应
DOI：
10.1061/9780784483961.015
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Sadri, Arif Mohaimin
中科院分区：
文献类型：
--
作者：
Linge, Priyanka;Rusho, M. Ahmed;Ahmed, Md. Ashraf;Sadri, Arif Mohaimin
2020 年，新冠肺炎 (COVID-19) 疫情肆虐，各国人民面临着前所未有的立即应对挑战。它深刻地震动了不同行业和整体经济。在这场疾病爆发期间，许多企业都关门了，但建筑业仍在继续运营，而其他行业则陷入困境。随着大流行的蔓延，随着人们开始保持身体距离并呆在家里，社交媒体互动的强度急剧增加。最近的研究表明，社交媒体的目的是在重大危机中传播信息，这种社交互动与现实世界中发生的事情相关。与传统媒体不同，社交媒体数据还提供了足够的统计能力来了解风险沟通模式。建筑行业采取创新战略来继续其运营和活动，同时应对与现场工人健康风险相关的一系列担忧。本研究旨在确定新冠肺炎 (COVID-19) 期间建筑利益相关者在社交媒体 (Twitter) 上新出现的沟通模式。在疫情持续流行的初期（2020 年 3 月、4 月和 5 月），Twitter 应用程序编程接口 (API) 在北美地区收集了约 1200 万条推文；然后根据与 COVID-19 和建筑活动相关的关键字过滤这些数据。这些信息是通过应用多种机器学习和自然语言处理技术来处理的。本研究揭示的建筑风险沟通的时空模式将支持政策制定者、企业和其他行业采取更有效的措施，并在当前和未来的流行病中更具弹性。
COVID-19 has spread rampantly in 2020 and people in different countries experienced unprecedented challenges to respond immediately. It has deeply shaken different industries and the overall economy. Many businesses were closed during this disease outbreak, but the construction industry continued to operate while others struggled. As the pandemic spread, the intensity of social media interactions dramatically increased as people started maintaining physical distances and staying at home. Recent studies have shown that social media serves the purpose of disseminating information in major crises and such social interactions correlate with what happens in the real world. Unlike traditional media, social media data also offered sufficient statistical power to understand risk communication patterns. The construction industry adopted innovative strategies to continue its operations and activities while responding to a number of concerns associated with health risks of the workers on site. This study aims at identifying the emerging communication patterns of construction stakeholders on social media (Twitter) during COVID-19. Around 12 million tweets were collected in the early days of the ongoing pandemic (March, April, and May 2020) by Twitter Application Programming Interface (API), in the region of North America; then filtered this data based on keywords pertaining to COVID-19 and construction activities. Such information was processed by applying several machine learning and natural language processing techniques. The spatiotemporal patterns of construction risk communication revealed in this study would support policymakers, businesses, and other industries to take more efficient measures and be more resilient both in the current and future pandemics.
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DOI：
10.1590/0102-311x00088120
发表时间：
2020-01-01
期刊：
Cadernos de Saúde Pública
影响因子：
--
作者：
Camargo Jr., Kenneth Rochel de
通讯作者：
Camargo Jr., Kenneth Rochel de
影响因子：
3
作者：
Mojumder, Md Nizamul Hoque;Ahmed, Md Ashraf;Sadri, Arif Mohaimin
通讯作者：
Sadri, Arif Mohaimin
影响因子：
2.8
作者：
Md Ashraf Ahmed;A. M. Sadri;Piyush Pradhananga;Mohamed Elzomor,;Nipesh Pradhananga
通讯作者：
Nipesh Pradhananga
桑迪飓风期间社交媒体的危机沟通模式
影响因子：
1.7
作者：
A. M. Sadri;Samiul Hasan;S. Ukkusuri;Manuel Cebrian
通讯作者：
Manuel Cebrian