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How Wikipedia disease information evolve over time? An analysis of disease-based articles changes

机译：维基百科疾病信息如何随着时间演变？基于疾病的文章变化分析

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摘要

Wikipedia, also known as "The Free Encyclopaedia", is one of the largest online repositories of biomedical information in the world, and is nowadays increasingly been used by medical researchers and health professionals alike. In spite of its rising popularity, little attention has been devoted to the understanding of how such medical information is organised, and especially how it evolves through time. We here present an analysis aimed at characterising such evolution, with a focus on the effects that such dynamic may have on an automated knowledge extraction process. For that, we start from a data set comprising a large number of snapshots of Wikipedia's disease articles, and the corresponding diagnostic elements as provided by the DISNET project Cdisnet.ctb.upm.es). We then track and analyse how different metrics evolve through time, such as the total article length or the number of medical terms and references. Results highlight some expected facts, as for instance that most articles increase their content through time; and that hot topics, as Alzheimer's disease, attract the highest number of editions and views. On the other hand, relevant behaviours are observed for less well-known diseases, including abrupt changes in the text and the concentration of contributions in a handful of editors. These results stress the importance of using correctly filtered and up-to-date datasets, and more general of considering the temporal evolution of the information in Wikipedia.
机译：维基百科，也被称为“免费百科全书”，是世界上最大的生物医学信息在线存储库之一，如今，医学研究人员和卫生专业人员越来越多地使用它。尽管它越来越受欢迎，但很少有人关注这种医疗信息的组织方式，尤其是它如何随着时间演变。我们在这里提出旨在表征这种进化的分析，重点是这种动态可能对自动化知识提取过程产生的影响。为此，我们从一个包含大量Wikipedia疾病文章快照和DISNET项目Cdisnet.ctb.upm.es提供的相应诊断元素的数据集开始。然后，我们跟踪并分析不同的指标如何随时间变化，例如文章的总长度或医学术语和参考文献的数量。结果突出了一些预期的事实，例如大多数文章会随着时间的推移增加其内容;而作为阿尔茨海默氏病的热门话题吸引了最多的刊物和观点。另一方面，对于不太为人所知的疾病，人们观察到了相关的行为，包括文本的突然变化和少数编辑的贡献集中。这些结果强调了使用正确过滤和最新的数据集的重要性，并且更普遍地考虑了Wikipedia中信息的时间演变。

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