Ethical issues in using Twitter for public health surveillance and research: developing a taxonomy of ethical concepts from the research literature.
Ethical issues in using Twitter for public health surveillance and research: developing a taxonomy of ethical concepts from the research literature.
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DOI：
10.2196/jmir.3617
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发表时间：
2014-12-22
影响因子：
7.4
通讯作者：
Conway, Mike
中科院分区：
文献类型：
--
作者：
Conway, Mike
背景技术背景：近年来社交媒体和微博平台的兴起，加上“大数据”处理和分析技术的发展，为利用用户生成的内容进行公共卫生监督提供了重要机会。然而，相对较少的注意力一直集中在开发道德上适当的方法来与这些新的数据sources.Objective：基于文献回顾，本研究旨在开发一个分类的公共卫生监督相关的伦理概念，出现时使用Twitter的数据，以期：（1）明确识别研究人员使用Twitter数据时可能出现的一系列潜在道德问题和担忧，和（2）提供一个起点，形成一套最佳实践的公共卫生监督，通过发展的经验派生分类的伦理概念。我们搜索Medline，Compendex，PsycINFO和哲学家的索引使用一组关键字选择，以确定Twitter相关的研究论文，引用伦理概念。我们最初的一组查询确定了四个书目数据库中的342个参考文献。我们使用我们的纳入/排除标准筛选这些参考文献的标题和摘要，排除重复和不可用的论文，直到保留49篇参考文献。然后，我们阅读了这49篇文章的全文，丢弃了36篇，最终纳入了13篇文章。然后在这13篇文章中确定了伦理概念。最后，基于对文本的仔细阅读，基于论文中发现的伦理概念构建了伦理概念的分类法。结果：从这13篇文章中，我们迭代地生成了由10个顶级类别组成的伦理概念的分类法：隐私，知情同意，伦理理论，机构审查委员会（IRB）/法规，传统研究与Twitter研究，地理信息，研究人员潜伏，经济价值的个人信息，医疗例外，并确定社会有害的医疗conditions.Conclusions的好处：总之，基于文献回顾，我们提出了一个临时分类的公共卫生监督相关的伦理概念，出现时使用Twitter的数据。
BACKGROUND: The rise of social media and microblogging platforms in recent years, in conjunction with the development of techniques for the processing and analysis of "big data", has provided significant opportunities for public health surveillance using user-generated content. However, relatively little attention has been focused on developing ethically appropriate approaches to working with these new data sources.OBJECTIVE: Based on a review of the literature, this study seeks to develop a taxonomy of public health surveillance-related ethical concepts that emerge when using Twitter data, with a view to: (1) explicitly identifying a set of potential ethical issues and concerns that may arise when researchers work with Twitter data, and (2) providing a starting point for the formation of a set of best practices for public health surveillance through the development of an empirically derived taxonomy of ethical concepts.METHODS: We searched Medline, Compendex, PsycINFO, and the Philosopher's Index using a set of keywords selected to identify Twitter-related research papers that reference ethical concepts. Our initial set of queries identified 342 references across the four bibliographic databases. We screened titles and abstracts of these references using our inclusion/exclusion criteria, eliminating duplicates and unavailable papers, until 49 references remained. We then read the full text of these 49 articles and discarded 36, resulting in a final inclusion set of 13 articles. Ethical concepts were then identified in each of these 13 articles. Finally, based on a close reading of the text, a taxonomy of ethical concepts was constructed based on ethical concepts discovered in the papers.RESULTS: From these 13 articles, we iteratively generated a taxonomy of ethical concepts consisting of 10 top level categories: privacy, informed consent, ethical theory, institutional review board (IRB)/regulation, traditional research vs Twitter research, geographical information, researcher lurking, economic value of personal information, medical exceptionalism, and benefit of identifying socially harmful medical conditions.CONCLUSIONS: In summary, based on a review of the literature, we present a provisional taxonomy of public health surveillance-related ethical concepts that emerge when using Twitter data.