在公共卫生领域,许多研究正在使用公开的Twitter数据进行,但是这些数据被用来回答的研究问题的类型以及这些项目需要道德监督的程度尚不清楚。
这篇综述从方法和研究问题的角度描述了使用Twitter数据进行公共卫生研究的现状,地理焦点,和道德方面的考虑,包括获得Twitter处理程序的知情同意。
我们实施了系统审查,遵循PRISMA(系统审查和荟萃分析的首选报告项目)指南,在2006年1月至2019年10月31日期间发表的文章中,使用Twitter数据进行公共卫生研究的二次分析,它们是使用Socindex上的标准化搜索标准找到的,PsycINFO,和PubMed。在使用Twitter进行主要数据收集时,研究被排除在外。例如用于研究招募或作为传播干预的一部分。
我们确定了367篇符合资格标准的文章。传染病(n=80,22%)和物质使用(n=66,18%)是这些研究中最常见的主题,和情绪挖掘(n=227,62%),监测(n=224,61%),主题探索(n=217,59%)是最常用的方法。大约三分之一的文章具有全球或全球地理重点;另外三分之一集中在美国。大多数(n=222,60%)的文章使用原生Twitter应用程序编程接口,和大量的剩余(n=102,28%)使用第三方应用程序编程接口。只有三分之一(n=119,32%)的研究寻求机构审查委员会的伦理批准,而其中17%(n=62)包括Twitter用户或推文的识别信息,其中36%(n=131)试图匿名标识符。大多数研究(n=272,79%)包括对编码的度量和可靠性的有效性的讨论(70%用于人类编码的互信度,70%用于计算机算法检查),但是对抽样框架的关注较少,以及样本代表的潜在人口。
Twitter数据可能对公共卫生研究有用,考虑到它对公开信息的访问。然而,研究在考虑数据源时应该更加谨慎,加入方法,和抽样框架的外部有效性。Further,需要一个伦理框架来帮助指导这一领域的未来研究,特别是当个人,可识别的Twitter用户和推文被共享和讨论。
PROSPEROCRD42020148170;https://www.crd.约克。AC.uk/prospro/display_record.php?RecordID=148170。
Much research is being carried out using publicly available Twitter data in the field of public health, but the types of research questions that these data are being used to answer and the extent to which these projects require ethical oversight are not clear.
This review describes the current state of public health research using Twitter data in terms of methods and research questions, geographic focus, and ethical considerations including obtaining informed consent from Twitter handlers.
We implemented a systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, of articles published between January 2006 and October 31, 2019, using Twitter data in secondary analyses for public health research, which were found using standardized search criteria on SocINDEX, PsycINFO, and PubMed. Studies were excluded when using Twitter for primary data collection, such as for study recruitment or as part of a dissemination intervention.
We identified 367 articles that met eligibility criteria. Infectious disease (n=80, 22%) and substance use (n=66, 18%) were the most common topics for these studies, and sentiment mining (n=227, 62%), surveillance (n=224, 61%), and thematic exploration (n=217, 59%) were the most common methodologies employed. Approximately one-third of articles had a global or worldwide geographic focus; another one-third focused on the United States. The majority (n=222, 60%) of articles used a native Twitter application programming interface, and a significant amount of the remainder (n=102, 28%) used a third-party application programming interface. Only one-third (n=119, 32%) of studies sought ethical approval from an institutional review board, while 17% of them (n=62) included identifying information on Twitter users or tweets and 36% of them (n=131) attempted to anonymize identifiers. Most studies (n=272, 79%) included a discussion on the validity of the measures and reliability of coding (70% for interreliability of human coding and 70% for computer algorithm checks), but less attention was paid to the sampling frame, and what underlying population the sample represented.
Twitter data may be useful in public health research, given its access to publicly available information. However, studies should exercise greater caution in considering the data sources, accession method, and external validity of the sampling frame. Further, an ethical framework is necessary to help guide future research in this area, especially when individual, identifiable Twitter users and tweets are shared and discussed.
PROSPERO CRD42020148170; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=148170.