How can you present network analysis results in an engaging way?

1 Choose the right layout

The layout of your network graph can have a big impact on how your audience perceives and interprets your results. Different layouts emphasize different aspects of the network, such as its clusters, communities, hubs, paths, or flows. Depending on your research question and the message you want to convey, you should choose a layout that best suits your purpose. For example, if you want to show the modularity of a network, you can use a force-directed layout that groups nodes by their connections. If you want to show the hierarchy of a network, you can use a tree or radial layout that arranges nodes by their levels. If you want to show the geospatial distribution of a network, you can use a map-based layout that plots nodes by their coordinates.

2 Use color and size wisely

Color and size are two of the most effective visual cues for highlighting and differentiating network elements. However, you should use them sparingly and consistently, to avoid cluttering and confusing your graph. A good practice is to use color and size to encode only one or two attributes of the nodes or edges, such as their degree, centrality, community, or weight. For example, if you want to show the importance of nodes in a network, you can use color to indicate their degree (the number of connections they have) and size to indicate their centrality (the influence they have on the network flow). You should also choose a color palette that is appropriate for your data type and audience. For example, if you have categorical data, you can use a qualitative palette that uses distinct colors for each category. If you have numerical data, you can use a sequential or diverging palette that uses shades of colors for different ranges of values.

3 Add labels and legends

Labels and legends are essential for providing context and meaning to your network graph. Without them, your audience may not understand what the nodes, edges, colors, and sizes represent. However, adding too many labels and legends can also make your graph look crowded and messy. Therefore, you should balance the trade-off between clarity and simplicity, and only include the most relevant and necessary information. For example, you can label only the most important nodes or edges in your network, such as the ones with the highest or lowest values of a certain attribute. You can also use abbreviations, icons, or symbols to save space and avoid overlapping. Moreover, you should make sure that your labels and legends are legible, consistent, and aligned with your graph. You can use fonts, colors, and styles that match your graph theme and contrast with your background.

4 Add interactivity and animation

Interactivity and animation are two powerful ways to enhance your network presentation and engage your audience. By adding interactivity, you can allow your audience to explore your network graph in more depth and detail, by zooming, panning, filtering, or selecting nodes and edges. By adding animation, you can show your audience how your network evolves over time, by changing the positions, colors, or sizes of nodes and edges. Both interactivity and animation can help you tell a more compelling and dynamic story with your network data, and reveal patterns and trends that may not be visible in a static graph. However, you should also be careful not to overuse or misuse interactivity and animation, as they can also distract or confuse your audience if they are not well designed and implemented. You should use interactivity and animation only when they serve a clear purpose and add value to your network analysis results.

5 Test and refine your graph

The final tip for improving your network presentation skills is to test and refine your graph before you share it with your audience. You should check your graph for accuracy, readability, and aesthetics, and make sure that it conveys your message clearly and effectively. You can also ask for feedback from your peers, colleagues, or potential audience members, and see how they interpret and react to your graph. You can use their feedback to identify and fix any issues or errors in your graph, and to enhance its strengths and features. By testing and refining your graph, you can ensure that it meets your expectations and goals, and that it delivers your network analysis results in an engaging way.