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Classification of abrupt changes along viewing profiles of scientific articles

机译:科学文章观察曲线突然变化的分类

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With the expansion of electronic publishing, a new dynamics of scientific articles dissemination was initiated. Still substantially important, citations became a longer term effect. Nowadays, many works are widely disseminated even before publication, in the form of preprints. Another important new element concerns the views of published articles. Thanks to the availability of respective data by some journals, such as PLoS ONE, it became possible to develop investigations on how scientific works are viewed along time, often before the first citations appear. This provides the main theme of the present work. More specifically, our research was motivated by preliminary observations that the view profiles along time tend to present a piecewise linear nature. A methodology was then delineated in order to identify the main segments in the view profiles, which allowed several related measurements to be derived. In particular, we focused on the inclination and length of each subsequent segment. Basic statistics indicated that the inclination can vary substantially along subsequent segments, while the segment lengths resulted more stable. Complementary joint statistics analysis, considering pairwise correlations, provided further information about the properties of the views. In order to better understand the view profiles, we performed respective multivariate statistical analysis, including principal component analysis and hierarchical clustering. The results suggest that a portion of the polygonal views are organized into clusters or groups. These groups were characterized in terms of prototypes indicating the relative increase or decrease along subsequent segments. Four respective distinct models were then developed for representing the observed segments. It was found that models incorporating joint dependencies between the properties of the segments provided the most accurate results among the considered alternatives.(c) 2021 Elsevier Ltd. All rights reserved.
机译:随着电子出版的扩展,启动了科学文章传播的新动态。仍然很重要,引文变得更长的效果。如今,即使在出版之前,许多作品也以预印迹的形式广泛传播。另一个重要的新元素涉及发表的文章的意见。由于某些期刊(例如PLOS)的各个期刊的可用性,它变得可以开发关于如何在第一个引用之前沿着时间看待科学作品的调查。这提供了本工作的主要主题。更具体地说,我们的研究是通过初步观察的推动,即沿着时间的视野概况倾向于提出分段的线性性质。然后描绘了一种方法,以便识别视图型材中的主要段,这允许达到几个相关的测量结果。特别是,我们专注于每个后续段的倾斜度和长度。基本统计表明,倾斜度可以大致沿后的段变化,而段长度导致更稳定。考虑成对相关性的互补联合统计分析提供了有关视图属性的更多信息。为了更好地理解视图配置文件,我们执行了各自的多变量统计分析,包括主成分分析和分层聚类。结果表明,将一部分多边形视图组织成簇或组。这些组的特征在于指示随后的段的相对增加或减少的原型。然后开发出四个相应的不同模型,用于代表观察到的段。结果发现,在段的性质之间结合联合依赖性的模型提供了考虑的替代方案中最准确的结果。(c)2021 Elsevier Ltd.保留所有权利。

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