Network plot frequently asked questions

Network plot frequently asked questions

What is a Network Plot ?
A Network Plot in Sigma Magic is a visual representation of relationships between data points (nodes) and their connections (edges). It helps analyze structures, dependencies, and groupings within a dataset.
What types of network plots can be created in Sigma Magic?
  • Undirected Graphs – where connections have no direction.
  • Directed Graphs – where edges show directional relationships.
  • Weighted Graphs – where edges have assigned values indicating connection strength.
  • Clustered Networks – showing community detection within the network.
What input data format is required for a Network Plot?

Sigma Magic uses an Edge List format, where data consists of two columns:

  • Column 1 (Source Node): The starting node.
  • Column 2 (Target Node): The connected node.
Example: 
Source
Target
A
B
B
C
A
D




How do I generate a Network Plot in Sigma Magic?
  1. Open Sigma Magic and go to the Network Plot module.
  2. Import the dataset in Edge List format.
  3. Select variables (source and target).
  4. Choose layout options (auto, circular, force-directed).
  5. Click Run Analysis to generate the plot.

How can I modify the layout of a Network Plot?
  • Auto Layout: Automatically adjusts positioning.
  • Circular Layout: Places nodes in a circle.
  • Force-Directed Layout: Uses physics-based positioning for readability.
  • Hierarchical Layout: Arranges nodes in levels based on connectivity.
How do I filter data in a network plot?
  • Node degree (number of connections).
  • Edge weight (threshold values).
  • Specific categories (filter by attributes).
    • What are centrality measures in network analysis?
  • Degree Centrality: Number of direct connections.
  • Betweenness Centrality: Importance in connecting different groups.
  • Closeness Centrality: How quickly a node can reach others.
    • How can I optimize a large network plot for readability?
    • Use Force-Directed Layout to spread nodes.
    • Filter nodes with low-degree connections.
    • Group similar nodes into clusters.

    How do I handle missing data in a Network Plot?
  • Remove nodes with no connections.
  • Replace missing values with estimated relationships.
  • Use default settings to ignore empty values.

    • How can I compare two network plots?
  • Generate two separate plots using different datasets.
  • Compare node centrality, cluster structures, and edge weights.

    • What are real-world applications of Network Plots?
  • ocial Media Analysis: Identifying influencers and communities.
  • Business Intelligence: Understanding supply chain relationships.
  • Cybersecurity: Detecting fraud networks and vulnerabilities.
  • Biological Networks: Mapping gene interactions.
  • Marketing Analysis: Customer segmentation based on interactions.
    •  
    Reference: Some of the text in this article has been generated using AI tools such as ChatGPT and edited for content and accuracy.

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