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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. 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