Two-layer visual analytics of truckers’ risk-coping social network

IF 1.8 4区计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Information Visualization Pub Date : 2024-08-03 DOI:10.1177/14738716241265110

Qi Huang, Mao Lin Huang, Yi-Na Li

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引用次数: 0

Abstract

Within organizations, managers’ specific responsibilities and domain expertise shape their interests in the output of social network analysis. Our proposed visualization approach is tailored to meet the operation-directed needs and preferences for visual analysis of specific tasks. This method prioritizes an overall geographical map with focal-contextual dynamics within the network. To enable a comprehensive and in-depth understanding of pinpointed focal areas, we customize an analytical framework for analyzing inter-community networks. We extract focal sub-networks from specific nodes to create graph visualization for detailed analysis, represent rich types of domain-specific graphic properties, and provide direct zoom+filtering interactions to allow easy pattern recognition and knowledge discovery. We applied our approach to visualizing the data from interactions among 300 city-based truck communities on the largest occupational platform for truckers in China. We also conduct a case study to demonstrate that our approach is effective in supporting managers’ network analysis and knowledge discovery.

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卡车司机风险应对社交网络的双层可视化分析

在组织内部，管理人员的具体职责和领域专长决定了他们对社会网络分析结果的兴趣。我们提出的可视化方法是为满足特定任务可视化分析的操作需求和偏好而量身定制的。这种方法优先考虑网络内具有焦点-上下文动态的整体地理图。为了能够全面深入地了解精确定位的重点区域，我们定制了一个用于分析社区间网络的分析框架。我们从特定节点中提取焦点子网络，创建用于详细分析的图形可视化，表现丰富的特定领域图形属性类型，并提供直接缩放和过滤互动，以方便模式识别和知识发现。我们将这一方法应用于中国最大的卡车司机职业平台上的 300 个城市卡车社区互动数据的可视化。我们还进行了一项案例研究，以证明我们的方法能够有效支持管理人员的网络分析和知识发现。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Information Visualization COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： Information Visualization is essential reading for researchers and practitioners of information visualization and is of interest to computer scientists and data analysts working on related specialisms. This journal is an international, peer-reviewed journal publishing articles on fundamental research and applications of information visualization. The journal acts as a dedicated forum for the theories, methodologies, techniques and evaluations of information visualization and its applications. The journal is a core vehicle for developing a generic research agenda for the field by identifying and developing the unique and significant aspects of information visualization. Emphasis is placed on interdisciplinary material and on the close connection between theory and practice. This journal is a member of the Committee on Publication Ethics (COPE).