Repository for Museums in the Pandemic (MIP): Risk, Closure, and Resilience

This repository contains Python code and data used in the Museums in the Pandemic (MIP) project, including aggregated social media datasets and analysis results. The input data cannot be disseminated for copyright reasons. <br> Project description: Museums have an important role in our economy, education and cultural life. They add to the texture and richness of villages, towns and cities, and can help build and maintain communities. During the pandemic, their continuing existence has been under threat, and while many museums have benefitted from emergency funding or government schemes, their position remains precarious. In order to better support the UK museum sector, the museum services need to identify which types of museums are at risk of closure, which remain resilient, and which close on a permanent basis. Doing so presents a considerable challenge. Data collection is selective and tends not to cover unaccredited museums, it is dispersed across multiple platforms, there are no mechanisms for documenting closure, and establishing risk of closure entirely relies on individual organisations self-reporting. The Museums in the Pandemic project investigates how ‘big data techniques’ can inform research into the UK museum sector. It combines qualitative and quantitative research, and has three inter-related strands: Developing new ways to collect data on museums. We will use web analytics, natural language processing, and sentiment analysis to digitally track trends as they emerge. The data will be analysed with respect to museum characteristics – such as governance, location and size – to provide a nuanced understanding of the sector at a given moment. Manually checking and validating the information generated by big data collection. Using interview-based research to better understand what constitutes risk during a pandemic, the triggers for permanent closure, and how museums have and continue to remain resilient. <br> URL: https://www.bbk.ac.uk/research/projects/museums-in-the-pandemic PI: Fiona Candlin (Birkbeck, UoL) Co-I: Andrea Ballatore (King's College London) Co-I: Alex Poulovassilis (Birkbeck, UoL) Co-I: Peter Wood (Birkbeck, UoL)

本仓库包含用于「疫情中的博物馆（Museums in the Pandemic, MIP）」项目的Python代码与数据集，其中涵盖聚合后的社交媒体数据集与分析结果。由于版权限制，输入数据集不得对外传播。

项目简介：博物馆在经济、教育与文化生活中扮演着关键角色。它们为乡村、城镇与城市增添了人文肌理与丰富内涵，亦有助于构建并维系社区联结。疫情期间，博物馆的存续面临威胁：尽管多数博物馆获得了应急资助或政府帮扶政策支持，其运营处境仍岌岌可危。为更好地支持英国博物馆行业，文博服务机构需明确哪些类型的博物馆面临关停风险、哪些具备运营韧性，以及哪些已永久闭馆。但此项工作面临诸多挑战：数据采集具有选择性，往往无法覆盖未获认证的博物馆；数据分散于多个平台；缺乏记录闭馆情况的标准化机制；且关停风险的判定完全依赖各机构自行上报。

「疫情中的博物馆」项目旨在探究大数据技术（big data techniques）如何为英国博物馆行业的研究提供支撑。本项目结合定性与定量研究方法，下设三个相互关联的研究分支：
1. 开发博物馆数据采集的新方法：我们将运用网络分析（web analytics）、自然语言处理（natural language processing）与情感分析（sentiment analysis）技术，对新兴趋势进行数字化追踪。后续将结合博物馆的治理模式、地理位置与规模等特征对采集到的数据开展分析，以精准刻画特定时期内行业的整体样貌。
2. 对大数据采集生成的信息进行人工核验与验证。
3. 基于访谈研究，深入解析疫情期间的关停风险成因、永久闭馆的触发因素，以及博物馆此前与当前维持运营韧性的路径。

项目网址：https://www.bbk.ac.uk/research/projects/museums-in-the-pandemic
项目负责人（Principal Investigator, PI）：菲奥娜·坎德林（伦敦大学伯克贝克学院，UoL）
联合项目负责人（Co-Investigator, Co-I）：安德里亚·巴拉托雷（伦敦国王学院）
联合项目负责人（Co-Investigator, Co-I）：亚历克斯·普洛夫瓦西利斯（伦敦大学伯克贝克学院，UoL）
联合项目负责人（Co-Investigator, Co-I）：彼得·伍德（伦敦大学伯克贝克学院，UoL）