Developing a standardized protocol for computational sentiment analysis research using health-related social media data
Developing a standardized protocol for computational sentiment analysis research using health-related social media data
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DOI：
10.1093/jamia/ocaa298
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发表时间：
2021-06-01
影响因子：
6.4
通讯作者：
Zheng, Kai
中科院分区：
文献类型：
--
作者：
He, Lu;Yin, Tingjue;Zheng, Kai
目的：情绪分析是分析与健康相关的社交媒体内容的流行工具。然而，现有的研究在研究设计和结果报告方面存在许多方法学问题和不一致之处，这可能导致数据偏倚，结论不准确或不正确，或研究结果不可比。本文报告了一个系统的分析文献就这些问题。目的是制定一个标准化的协议，以提高研究的有效性和结果的可比性，在未来的相关研究。材料和方法：我们开发了一个协议的分析健康的感觉（PATH）的基础上，分析了常见的研究设计的选择，以及如何这样的选择，或报告，在2010年至2019年发表的合格的研究。在筛选的409篇文章中，89篇符合纳入标准。共确定了16种独特的研究设计选择，其中9种在所审查的文章中具有显著的方法或报告不一致性，从如何确定研究数据的相关性到如何验证所选择的情感分析工具。基于这一结果，我们开发了PATH协议，包括所有这些独特的设计选择，并强调了那些仔细考虑和详细的报告是特别warranted.Conclusions：在现存的文献中，情绪分析，分析健康相关的社交媒体数据的方法和报告存在很大程度的不一致。通过本研究开发的PATH协议可能有助于在未来的相关研究中缓解此类问题。
Objective: Sentiment analysis is a popular tool for analyzing health-related social media content. However, existing studies exhibit numerous methodological issues and inconsistencies with respect to research design and results reporting, which could lead to biased data, imprecise or incorrect conclusions, or incomparable results across studies. This article reports a systematic analysis of the literature with respect to such issues. The objective was to develop a standardized protocol for improving the research validity and comparability of results in future relevant studies.Materials and Methods: We developed the Protocol of Analysis of senTiment in Health (PATH) based on a systematic review that analyzed common research design choices and how such choices were made, or reported, among eligible studies published 2010-2019.Results: Of 409 articles screened, 89 met the inclusion criteria. A total of 16 distinctive research design choices were identified, 9 of which have significant methodological or reporting inconsistencies among the articles reviewed, ranging from how relevance of study data was determined to how the sentiment analysis tool selected was validated. Based on this result, we developed the PATH protocol that encompasses all these distinctive design choices and highlights the ones for which careful consideration and detailed reporting are particularly warranted.Conclusions: A substantial degree of methodological and reporting inconsistencies exist in the extant literature that applied sentiment analysis to analyzing health-related social media data. The PATH protocol developed through this research may contribute to mitigating such issues in future relevant studies.