Tracking Museums' Online Responses to the COVID-19 Pandemic: A Study in Museum Analytics
Tracking Museums' Online Responses to the COVID-19 Pandemic: A Study in Museum Analytics
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DOI：
10.1145/3627165
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发表时间：
2024-03-01
影响因子：
2.4
通讯作者：
Wood，Peter T.
中科院分区：
文献类型：
--
作者：
Ballatore，Andrea;Katerinchuk，Valeri;Wood，Peter T.
新冠肺炎疫情导致英国所有博物馆暂时关闭，关闭建筑物，暂停所有现场活动。在长期数据匮乏的背景下，博物馆机构的目标是减轻和管理这些对该部门的影响。“大流行中的博物馆”是一个跨学科项目，利用从博物馆网站和社交媒体帖子中抓取的内容，了解目前由3300多家博物馆组成的英国博物馆部门如何应对和目前正在应对大流行。该项目的一个主要部分是设计计算技术，为该项目的博物馆研究专家提供适当的数据和工具，以利用网络分析、自然语言处理和机器学习进行这项研究。在这一方法论贡献中，首先，我们开发了检索和识别博物馆官方网站和社交媒体账户（现在是Facebook和Twitter）的技术。这支持了对整个英国博物馆部门的大规模在线数据的自动捕获。其次，我们利用卷积神经网络从非结构化文本中提取活动指标，以检测博物馆的行为，包括开放、关闭、筹款和人员配备。这个动态数据集使团队中的博物馆研究专家能够根据博物馆的规模、治理、认证和位置，研究大流行之前、期间和之后博物馆在线存在的模式。
The COVID-19 pandemic led to the temporary closure of all museums in the UK, closing buildings and suspending all on-site activities. Museum agencies aim at mitigating and managing these impacts on the sector, in a context of chronic data scarcity. “Museums in the Pandemic” is an interdisciplinary project that utilises content scraped from museums’ websites and social media posts to understand how the UK museum sector, currently comprising more than 3,300 museums, has responded and is currently responding to the pandemic. A major part of the project has been the design of computational techniques to provide the project’s museum studies experts with appropriate data and tools for undertaking this research, leveraging web analytics, natural language processing and machine learning. In this methodological contribution, firstly, we developed techniques to retrieve and identify museum official websites and social media accounts (Facebook and Twitter now X). This supported the automated capture of large-scale online data about the entire UK museum sector. Secondly, we harnessed convolutional neural networks to extract activity indicators from unstructured text to detect museum behaviours, including openings, closures, fundraising and staffing. This dynamic dataset is enabling the museum studies experts in the team to study patterns in the online presence of museums before, during, and after the pandemic, according to museum size, governance, accreditation and location.