Leveraging my Network
LinkedIn is a great concept, in theory. Building and maintaining a robust network should be highly beneficial to all involved, but it can be difficult to maintain as it grows over time. I have committed to myself that I would get better at both leveraging and nurturing the network I have developed over the years and felt a good start would be to step back and visualize it in some manner.
(this is not my network)
In the past, LinkedIn has a project called InMaps, but for some reason they discontinued it years ago (2014). It was a really interesting way of visualizing how your network was clustered...but honestly, there was much business value. (I pretty much already knew I had a bunch of Mercury and Applause contacts.)
A was googling around for alternative and found this data visualization project by Tavish Gobindram. It uses a Jupyter Notebook, and since we have been talking about these a lot at work lately (building skill assessments for Data Science candidates at Codility), I wanted to investigate a little further and try it for myself.
I was amazed at how easy is was to replicate Tavish's project. A couple of installs and a download or two later, I has a visualization of my LinkedIn Network.
(this is my network)
While this was a fun project, the problem is it didn't expose any information I didn't already really know. What I would like to uncover relates to the people my contact know...and their contacts. (For example, I would like it to tell me that I am only three degrees away from the Queen of England or the Pope...but already know that, too). Perhaps I will need to combine this with my recent Python webscraping project (more on that another day).
After I played with this for a while...and started verifying the data in the exported CSV file of connections, I actually found that this was where the interesting stuff existed. I sorted the names by "connected on" date and began to review where my contacts have landed after 16 years of connecting. This "scroll" though memory lane was insightful...and much faster that clicking through pages on the LinkedIn site.
If you know of better solutions for exploring your LinkedIn network, please tell me it in the comments. Otherwise, feel free to use the info above to explore your network and dip your toes into the Data Visualization ocean.
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3 年I've found kumu.io, as seen on a video, you can add your buddy's, your colleagues' Linkedin connection csv to it, and will give something, or even better than InMaps was. The coloring is different, but as it seems, the end result is GOOD. ??
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3 年I loved InMaps. I still haven't found anything quite like it. Thank you for sharing this article.