Usher Institute, The University of Edinburgh, Edinburgh, United Kingdom.
School of Computing, Edinburgh Napier University, Edinburgh, United Kingdom.
J Med Internet Res. 2021 May 17;23(5):e26618. doi: 10.2196/26618.
The emergence of SARS-CoV-2 in late 2019 and its subsequent spread worldwide continues to be a global health crisis. Many governments consider contact tracing of citizens through apps installed on mobile phones as a key mechanism to contain the spread of SARS-CoV-2.
In this study, we sought to explore the suitability of artificial intelligence (AI)-enabled social media analyses using Facebook and Twitter to understand public perceptions of COVID-19 contact tracing apps in the United Kingdom.
We extracted and analyzed over 10,000 relevant social media posts across an 8-month period, from March 1 to October 31, 2020. We used an initial filter with COVID-19-related keywords, which were predefined as part of an open Twitter-based COVID-19 dataset. We then applied a second filter using contract tracing app-related keywords and a geographical filter. We developed and utilized a hybrid, rule-based ensemble model, combining state-of-the-art lexicon rule-based and deep learning-based approaches.
Overall, we observed 76% positive and 12% negative sentiments, with the majority of negative sentiments reported in the North of England. These sentiments varied over time, likely influenced by ongoing public debates around implementing app-based contact tracing by using a centralized model where data would be shared with the health service, compared with decentralized contact-tracing technology.
Variations in sentiments corroborate with ongoing debates surrounding the information governance of health-related information. AI-enabled social media analysis of public attitudes in health care can help facilitate the implementation of effective public health campaigns.
2019 年末 SARS-CoV-2 的出现及其随后在全球范围内的传播，持续构成全球卫生危机。许多政府认为，通过在移动电话上安装应用程序对公民进行接触者追踪，是遏制 SARS-CoV-2 传播的关键机制。
本研究旨在探索使用 Facebook 和 Twitter 进行人工智能 (AI) 支持的社交媒体分析，以了解英国公众对 COVID-19 接触者追踪应用程序的看法。
我们在 2020 年 3 月 1 日至 10 月 31 日的 8 个月期间，提取和分析了超过 10000 条相关的社交媒体帖子。我们使用了一个带有 COVID-19 相关关键字的初始筛选器，这些关键字是作为基于开放的 Twitter 的 COVID-19 数据集的一部分预先定义的。然后，我们使用与接触者追踪应用程序相关的关键字和地理位置筛选器应用了第二个筛选器。我们开发并利用了一种混合的、基于规则的集成模型，结合了最先进的词汇规则和基于深度学习的方法。
总体而言，我们观察到 76%的积极情绪和 12%的消极情绪，其中大部分负面情绪报告来自英格兰北部。这些情绪随时间而变化，可能受到有关实施基于应用程序的接触者追踪的持续公共辩论的影响，这些辩论涉及使用数据将与卫生服务共享的集中模型，与分散式接触追踪技术相比。
情绪的变化与围绕健康相关信息的信息治理的持续辩论相符。AI 支持的社交媒体分析公众对医疗保健的态度可以帮助促进有效的公共卫生运动的实施。
