Semantic Map and Network Graph
The Semantic Map and Network Graph feature in Cardus.AI allows you to interactively visualize the relationships between narratives, tags, clusters, and interview categories. This visualization provides a structural representation of the dataset, making visible connections, overlaps, and patterns that are not easily perceived in lists or tables.
Key Features
- Relational Visualization: Explore how narratives, tags, clusters, sentiment values and categories relate to one another
- Interactive Semantic Map: Navigate the project’s semantic space, observing proximity and grouping between elements
- Network Graph: View the data as a network of nodes and connections, highlighting relationships formed during the classification
- Multi-Level Exploration: Switch between more aggregated views (clusters, tags) and more granular views (individual narratives)
Benefits
- Make Relationships Explicit: Reveal recurring connections between themes, experiences, and sets of narratives
- Identify Overlaps and Tensions: Observe where tags and clusters intersect or concentrate within specific interview categories
- Support Non-Linear Exploration: Allow analysis to follow multiple paths rather than a fixed sequence of filters
- Complement Metrics and Tables: Enrich quantitative analysis with a structural and relational view of the data
How to use
- Select the Visualization Type: Choose between the Semantic Map or the Relationship Graph
- Define the Initial Focus: Start from a clusters, tags, sentiment or categories, choose full screen, with or without legends and labels
- Explore Connections: Navigate visible relationships, expanding or collapsing nodes as needed, zoom in and out, read each narrative if need it