Uncovering User Communities

Clustering algorithms can reveal distinct user communities. In visualized graphs, these communities are often represented by different colours. Larger clusters are typically found at the centre of the graph, while smaller, more targeted clusters form on the periphery. Each cluster represents users with similar interests, and analysing these clusters can provide insights into niche communities within the larger network.

Clustering Example

Consider a Pinterest analysis focused on fashion. The graph might show:

• Central clusters: Representing users with diverse interests or highly connected users.
• Peripheral clusters: Representing niche communities with more focused content. Each cluster is colour-coded, revealing insights into the subtopics of interest, such as fashion trends, sustainable fashion, or seasonal styles.