Visualize your LinkedIn network with InMaps
If you're a LinkedIn user, you already know the power of your professional network. — What if you could visualize what your network looks like? Would your connections form clusters or groups? Wouldn't it be great if you could see the way …
Context & Ripple Effects
LinkedIn has spent three years making its member graph more legible. Its 2008 Company Detail pages exposed where people moved between Silicon Valley firms, and a year ago it rebuilt the way members browse their connections. InMaps extends that line from lists to pictures: the tool renders a member's entire network as labeled clusters.
The significance is directional rather than incremental — each step hands members a richer view of the same underlying data, and InMaps is the first to show the graph's shape rather than its contents. As the Read/WriteWeb debate over business networking in 2007 framed it, the question was always what a professional network was actually worth; tools like this make the answer visible.
First-order effects
- Members gain a map-level view of their own connections as clusters, completing the shift LinkedIn began with its 2010 connection-browsing overhaul.
- For LinkedIn, InMaps turns the member graph itself into a consumer-facing product surface rather than just the plumbing behind search and profile views.
Second-order effects
- Clustered views of who-knows-whom give LinkedIn a template for packaging graph structure at the organizational level, extending the firm-mobility picture its 2008 Company Detail pages already sketched.
Third-order effects
- If visualization proves sticky, professional graphs become analytics assets in their own right — pressuring every business-networking platform to decide whether graph-derived insight stays free navigation or becomes a monetizable product line.
The trend: Professional-networking platforms are progressively converting their social graphs from invisible infrastructure into user-visible analytics products.