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Micro diagrams: visualization of categorical point data from location-based social media
Cartography and Geographic Information Science ( IF 2.354 ) Pub Date : 2020-03-10 , DOI: 10.1080/15230406.2020.1733438
Mathias Gröbe 1 , Dirk Burghardt 1
Affiliation  

ABSTRACT

Location-based social media data from different platforms such as Twitter and Flickr increasingly serve with their point-geocoded content as data sources for a variety of applications. The standard visualization method uses a derivation of point maps, which works well with a limited amount of data, but it suffers from weaknesses related to cluttering and overlapping, especially for sets of categories. We developed a new visualization method for categorical point data, called “Micro Diagrams”, which uses small diagrams to show the percentages of categories and the spatial distribution. The processing steps to derive the micro diagrams start with aggregating the points in a regular grid structure, which is followed by the selection of the diagram type that represents the numerical proportions and the application of a size scaling function to show the amounts of data. Various parameterization options are discussed and the influence of the color selection is analyzed. Finally, a case study combined with a user test presents the strengths and limits of the micro diagram method.



中文翻译:

微型图:基于位置的社交媒体中分类点数据的可视化

摘要

来自不同平台(例如Twitter和Flickr)的基于位置的社交媒体数据越来越多地以其点地理编码的内容作为各种应用程序的数据源。标准的可视化方法使用点图的派生,这种方法可以在有限的数据量下很好地工作,但是存在与混乱和重叠有关的弱点,尤其是对于类别集。我们为分类点数据开发了一种新的可视化方法,称为“微图”,该方法使用小图显示类别的百分比和空间分布。导出微图的处理步骤始于将规则网格中的点聚合在一起,接下来是选择表示数值比例的图表类型,并应用大小缩放功能来显示数据量。讨论了各种参数化选项,并分析了颜色选择的影响。最后,结合用户测试的案例研究展示了微图方法的优势和局限性。

更新日期:2020-03-10
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