The paper problematises the reliability and ethics of using social media data, such as sourced from Twitter or Instagram, to carry out health-related research. As in many other domains, the opportunity to mine social media for information has been hailed as transformative for research on well-being and disease. Considerations around the fairness, responsibilities and accountabilities relating to using such data have often been set aside, on the understanding that as long as data were anonymised, no real ethical or scientific issue would arise. We first counter this perception by emphasising that the use of social media data in health research can yield problematic and unethical results. We then provide a conceptualisation of methodological data fairness that can complement data management principles such as FAIR by enhancing the actionability of social media data for future research. We highlight the forms that methodological data fairness can take at different stages of the research process and identify practical steps through which researchers can ensure that their practices and outcomes are scientifically sound as well as fair to society at large. We conclude that making research data fair as well as FAIR is inextricably linked to concerns around the adequacy of data practices. The failure to act on those concerns raises serious ethical, methodological and epistemic issues with the knowledge and evidence that are being produced.

该论文对使用社交媒体数据（例如来自Twitter或Instagram）进行健康相关研究的可靠性和道德提出了质疑。像在许多其他领域一样，挖掘社交媒体获取信息的机会被誉为对福祉和疾病研究的变革。人们常常将关于使用此类数据的公平性，责任和问责制的考虑搁置一旁，但要理解的是，只要对数据进行匿名处理，就不会出现真正的道德或科学问题。我们首先通过强调在健康研究中使用社交媒体数据会产生有问题和不道德的结果来反驳这种看法。然后，我们提供方法数据公平性的概念化可以通过增强社交媒体数据的可操作性来补充数据管​​理原则（例如FAIR），以供将来研究之用。我们重点介绍了方法学数据公平性在研究过程的不同阶段可以采取的形式，并确定了研究人员可以确保其实践和结果在科学上合理且对整个社会公平的实际步骤。我们得出结论，使研究数据既公平又公平，与对数据实践充分性的担忧密不可分。如果不采取这些行动，就会产生严重的道德，方法论和认识论问题，并带有正在产生的知识和证据。