3 Ways To Meaningfully Visualize Your LinkedIn Network

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LinkedIn has always been one of the most useful social media networks for me. The reason is simple: it is business-oriented and (almost) clutter-free. While I do have a large network there, I am almost never spammed or bugged in any way: there no random people who are willing to chat or pitch their products.

The best thing is that people are connected for a reason there: when sending a friend request, you need to specify how you are connected to a person. This way your network contains a wealth of business-oriented information: you can find out how you are related to any company or person you need to get in touch with. Alternatively, you can be introduced to anyone outside your immediate network using your first-level connections.

Tapping into your Linkedin connections can be a great way to discover new career opportunities for personal and professional growth � and here are three tools that can help you to:

1. Visualize Your Network Layers and Influencers: InMaps

InMaps (we have already reviewed InMaps) is a new project inside LinkedIn labs that creates the visual representation of your professional network. The tool goes through your connections, analyzes the links between them and groups them into different network clusters.

It may take some time for larger networks but it is well worth waiting�

The tool can be a huge help in identifying influencers in your business network:

People with bigger dots and their names in larger fonts have more connections;
Click on any dot to see the person you are connected to as well as where your points of connection overlap.

Besides that, your map is color-coded to represent different affiliations or groups from your professional career, such as your previous employer, college classmates, or industries you've worked in.

The tool thus turns really helpful for building and expending your reach on many levels but most importantly, it adds some context to your connections: learn why people know each other and how they are connected.

2. Visualize Your Relation to Any Company: MyWebCareer

MyWebCareer is a multi-feature tool that makes sense of your Linkedin and Facebook connections by using sophisticated link analysis, visualization, and semantics technologies

All the content the tools retrieves from your LinkedIn profile is fed into the semantic and entity extraction engine. The output enables you to explore a merged view of your online presence across multiple Internet properties and search engines.

For example, the tool lets you identify your top companies you are associated with as well as top industry you are involved with:

While the above visualization and graphing tools look interesting, the best tool inside is called "My Network" that provides visual interface for exploring your merged Career & Social Graph. It can turn very useful for exploring your relation to any company in your network.

Click on any company name in the list and the tool will show which of your connections is involved in it and how:

Red Links = current position
Blue Links = previous positions
Link Thickness = time at company

If you also have Facebook account tied to MyWebCareer, you'll be able to see if you are connected to the person through Linkedin or Facebook or both.

For example, here are my LinkedIn contacts who are related to About.com. You can see how long they have been involved into the company, if the are currently working there and how you are connected:

3. Visualize Company and Position Distribution: ManyEyes

ManyEyes (here's our review of ManyEyes) is a multi-purpose free visualization tool that can process and graph any data you provide. With LinkedIn, you can export the whole list of your connections using AddressBookExport tool. The list will contain:

The full name of each of your contact;
The email address;
The current position;
The company.

The latter two can become a great source for visualization (especially for large networks).

Just format your .CSV file a bit. In my case that was merely about:

Breaking data into columns using comma as delimiter;
Adding informative column headers;
(Possibly) deleting unnecessary rows.

Then copy-paste the area with data into ManyEyes and make sure the data is properly processed using the preview:

Now, choose the visualization type and pattern (there are plenty of those inside). I chose the Matrix Chart that allowed me to visualize position versus company distribution using colors: