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<p>Analysis of user groups in geosocial media data presents significant methodological challenges, as users can be characterized by numerous attributes, the combinations of which produce complex group structures. Conventional visualization techniques often struggle to represent such multidimensional attribute combinations and to support the visual analysis of relevant groups. The FacetWheel addresses this limitation through a&#xa0;set-oriented data model, representing user groups as intersections of discrete attribute values. Its visual design follows a&#xa0;radial metaphor: attributes are arranged in a&#xa0;circle, with their attribute values shown as color-coded rectangles. Groups are represented by rectangles or appear as connecting lines, the width of which encodes group size. To reduce visual complexity and facilitate targeted pattern detection, interactive tools are provided. The integration of the overlap coefficient enables a&#xa0;quantitative assessment of group overlaps, an aspect rarely addressed in comparable visualization methods. Supplementary map and timeline views extend the analysis to spatial and temporal dimensions. This integration expands traditional cartographic approaches, which typically visualize single attributes or aggregated categories, by enabling the exploration of multidimensional, set-based groups in their spatial and temporal context. A&#xa0;case study demonstrates that the FacetWheel can address a&#xa0;wide range of analytical questions concerning the structure, size, and distribution of user groups. While the visualization has limitations when selecting very small groups, it offers improved scalability, interpretability, and quantifiability. Overall, the FacetWheel provides a&#xa0;visually differentiated interactive environment for exploring complex group structures, opening new perspectives for data-driven spatial and temporal research on geosocial media.</p>

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FacetWheel—Characterization and Visual Exploration of User Groups from Geosocial Media Data

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年3月6日

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  • Thomas Gründemann,
  • Dirk Burghardt

摘要

Analysis of user groups in geosocial media data presents significant methodological challenges, as users can be characterized by numerous attributes, the combinations of which produce complex group structures. Conventional visualization techniques often struggle to represent such multidimensional attribute combinations and to support the visual analysis of relevant groups. The FacetWheel addresses this limitation through a set-oriented data model, representing user groups as intersections of discrete attribute values. Its visual design follows a radial metaphor: attributes are arranged in a circle, with their attribute values shown as color-coded rectangles. Groups are represented by rectangles or appear as connecting lines, the width of which encodes group size. To reduce visual complexity and facilitate targeted pattern detection, interactive tools are provided. The integration of the overlap coefficient enables a quantitative assessment of group overlaps, an aspect rarely addressed in comparable visualization methods. Supplementary map and timeline views extend the analysis to spatial and temporal dimensions. This integration expands traditional cartographic approaches, which typically visualize single attributes or aggregated categories, by enabling the exploration of multidimensional, set-based groups in their spatial and temporal context. A case study demonstrates that the FacetWheel can address a wide range of analytical questions concerning the structure, size, and distribution of user groups. While the visualization has limitations when selecting very small groups, it offers improved scalability, interpretability, and quantifiability. Overall, the FacetWheel provides a visually differentiated interactive environment for exploring complex group structures, opening new perspectives for data-driven spatial and temporal research on geosocial media.