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Identifying the skeptics and the undecided through visual cluster analysis of local network geometry

Visual Informatics 2022年第3期6卷 11-22页

作者： Shenghui Cheng Joachim Giesen Tianyi Huang Philipp Lucas Klaus Mueller Westlake University HangzhouChina Stony Brook University NYUnited States of America Friedrich-Schiller-Universitat Jena JenaGermany Westlake Institute for Advanced Study HangzhouChina Research Center for the Industries of the Future HangzhouChina

By skeptics and undecided we refer to nodes in clustered social networks that cannot be assigned easily to any of the *** nodes are typically found either at the interface between clusters(the undecided)or at their boundaries(the skeptics).Identifying these nodes is relevant in marketing applications like voter targeting,because the persons represented by such nodes are often more likely to be affected in marketing campaigns than nodes deeply within *** far this identification task is not as well studied as other network analysis tasks like clustering,identifying central nodes,and detecting *** approach this task by deriving novel geometric features from the network structure that naturally lend themselves to an interactive visual approach for identifying interface and boundary nodes.

关键词： Graph/network data high dimensional data visualization visualization in social and information sciences data clustering coordinated and multiple views

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Geo-Coordinated Parallel Coordinates (GCPC): Field trial studies of environmental data analysis

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Visual Informatics 2018年第2期2卷 111-124页

作者： Maha El Meseery Orland Hoeber University of Regina Canada

The large number of environmental problems faced by society in recent years has driven researchers to collect and study massive amounts of data in order to understand the complex relations that exist between people and the environment in which we *** datasets are often high dimensional and heterogeneous in nature,with complex geospatial *** such data can be challenging,especially when there is a need to maintain spatial awareness as the non-spatial attributes are ***-Coordinated Parallel Coordinates(GCPC)is a geovisual analytics approach designed to support exploration and analysis within complex geospatial environmental *** coordinates are tightly coupled with a geospatial representation and an investigative scatterplot,all of which can be used to show,reorganize,filter,and highlight the high dimensional,heterogeneous,and geospatial aspects of the *** sets of field trials were conducted with expert data analysts to validate the real-world benefits of the approach for studying environmental *** results of these evaluations were positive,providing real-world evidence and new insights regarding the value of using GCPC to explore among environmental datasets when there is a need to remain aware of the geospatial aspects of the data as the non-spatial elements are studied.

关键词： Geovisual analytics Heterogeneous data visualization high dimensional data visualization Field trial evaluations

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