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| name | network-computation-expert |
| description | 社会网络计算专家分析技能，整合网络数据处理、网络构建、中心性分析、社区检测和网络可视化功能，提供全面的网络分析框架 |
| version | 1.0.0 |
| author | socienceAI.com |
| license | MIT |
| tags | ["network-analysis","social-networks","centrality","community-detection","visualization","network-computation"] |
| compatibility | Claude 3.5 Sonnet and above |
| metadata | {"domain":"social-network-analysis","methodology":"network-analysis","complexity":"advanced","integration_type":"analysis_tool","last_updated":"2025-12-27"} |
| allowed-tools | ["python","bash","read_file","write_file"] |
社会网络计算专家分析技能整合了网络数据处理、网络构建、中心性分析、社区检测和网络可视化功能，为社会科学研究提供全面的网络分析框架。该技能帮助研究者从原始数据到网络分析结果的全流程处理。
当用户请求以下分析时使用此技能：
当用户请求网络分析时：
network_format: 输入格式 (edgelist, adjacency matrix, JSON等)directed: 网络是否有向 (默认: false)weighted: 网络是否加权 (默认: true)centrality_metrics: 要计算的中心性指标列表community_method: 社区检测算法visualization_type: 可视化类型 (静态, 交互式)node_attributes: 用于可视化的额外节点属性edge_attributes: 用于可视化的额外边属性methodology: 分析方法 (定量, 定性, 混合)cultural_context: 文化背景考虑 (特别是中文研究背景)User: "分析组织内部的沟通网络" Response: 处理沟通数据，构建网络，计算中心性指标，检测社区结构，生成可视化。
User: "分析社交媒体中的影响力网络" Response: 提取关系数据，构建网络，识别关键影响者，检测社区，分析传播路径。
User: "分析学术合作网络的结构" Response: 处理合作数据，构建网络，计算中心性，检测研究群体，分析合作模式。
{
"summary": {
"total_nodes": 50,
"total_edges": 120,
"network_density": 0.098,
"components": 1,
"avg_path_length": 2.34,
"diameter": 6,
"modularity": 0.72,
"top_centrality_node": "节点A"
},
"details": {
"network_processing": {...},
"network_construction": {...},
"centrality_analysis": {...},
"community_detection": {...},
"visualization_data": {...}
},
"metadata": {
"timestamp": "2025-12-27T10:30:00",
"version": "1.0.0"
}
}
skills/network-computation-expert/scripts/network_analyzer.py完成高质量的网络分析应包括：
此技能为社会科学研究提供专业的综合网络分析框架和工具，确保研究的科学性和严谨性。