Social listening: Applying natural language processing methods to social media data to yield actionable analytics for health and care services

了解公众对使用信息技术和健康数据的意见和偏好是至关重要的，这是设计未来医疗保健和研究模式的一部分。社交媒体平台（如Twitter）、博客和在线讨论论坛提供了自然发生的对话的丰富资源，用于审查公众对以下两种情况的态度和偏好：（a）作为医疗保健服务一部分的信息和数字技术;（B）将健康数据用于直接医疗保健以外的目的，如研究。可以使用既定的定性研究技术手动分析公众评论和对话。虽然这些方法提供了深度和严谨性，但它们通常是劳动密集型的，并且在没有显著努力和资源的情况下既不能快速应用也不能大规模应用。我建议研究自然语言处理（NLP）领域有前途的新技术，以快速自动地分析公众对公共社交媒体数据中的健康和护理的态度和偏好的文本数据。我将比较NLP方法与既定的定性方法的性能，并评估这两种方法如何相互补充，以收集对公众舆论的见解，用于持续的监测，研究，评估和告知公共政策。我将测试先进的数据可视化方法来报告我的发现。利用我的网络，我将探索如何将我的工作转化为更广泛的应用，在英国健康数据研究，医疗服务和国际。在整个项目中，我将遵守使用社交媒体数据的道德准则，并将让相关社区（在线和离线）的公民参与研究的设计和交付。

It is vital to understand public opinion and preferences towards the use of information technology and health data as part of designing future models of healthcare and research. Social media platforms (e.g. Twitter), blogs and online discussion forums provide a rich resource of naturally occurring conversations for examining public attitudes and preferences towards (a) information and digital technologies as part of the delivery of healthcare and (b) the secondary use of health data for purposes beyond direct healthcare, such as research. Analysing public comments and conversations can be analysed manually using established qualitative research techniques. Whilst such methods provide depth and rigour, they are typically labour intensive and can neither be applied rapidly nor on a large scale basis without significant effort and resource. I propose to investigate promising new techniques from the field of natural language processing (NLP) to rapidly and automatically analyse textual data about public attitudes and preferences towards health and care from publicly available social media data. I will compare the performance of NLP methods against established, qualitative approaches and assess how the two approaches can complement each other to gather insights into public opinion for the purposes of ongoing monitoring, research, evaluation and informing public policy. I will test advanced methods of data visualisation to report my findings. Leveraging my networks, I will explore how to translate my work into wider applications, within Health Data Research UK, healthcare services and internationally. Throughout the project I will adhere to ethical guidelines for using social media data and will involve citizens from relevant communities (online and offline) in shaping the design and delivery of the research.