LinkedIn Insights
This project utilizes Tableau to explore and analyze my own LinkedIn data.
LinkedIn Insights2
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I remember when I was first introduced to LinkedIn way back when it was new. And I remember wondering how or why I would ever find myself using this tool, at the time. Oh how my life has changed since then!
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In today's digital age, social media platforms like LinkedIn have become an integral part of professional networking and job search. However, beyond just connecting with people, LinkedIn also stores a wealth of data about our activities on the platform, including our profile views, connections, and post engagements. By analyzing this data, we can gain insights into our networking patterns, audience preferences, and overall engagement levels. In this article, I will explore the process of analyzing my own LinkedIn data and how it can be used to optimize my professional presence on the platform.
Using my own LinkedIn data, I was able to determine the following:
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There are only a few people who I message often, I limited the graph to the top ten.
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November 13, 2022 was my peak connection request day with a total of 81 requests.
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My connections work at a diverse collection of companies.
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My most common connection type are other Data Analysts, 76 in total.
First, the Data!
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Getting a copy of your LinkedIn data is as simple as requesting it in the "Settings and Privacy" portion of your LinkedIn account. If you would like to do a similar project, please plan ahead and request this information at least 24 hours in advance.
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Then, when the download is ready you will receive a zip file with about 38 csv files and three folders of rich information about all aspects of your LinkedIn profile and usage.
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For the purposes of this project, I mainly utilized the "messages" and the "connections" csv files.
The Analysis
My first interest was to see who it is that I'm messaging the most often on LinkedIn. Instead of keeping the entire graph, I decided to limit it to the top ten individuals with whom I correspond the most using this platform.
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Next, I turned my attention to creating a visualization to figure out how many of my connections have the same first name. I ended up not utilizing this graph in the dashboard because there were no overwhelmingly common names.
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Another relationship that interested me was how many of my connections worked at the same company. I discovered that my connections work at a wide variety of companies, so I decided to include the top ten companies in this treemap.
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How did I achieve the 855 connections I now have? The following chart shows the progression of connecting with others over time.
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Out of curiosity, I wanted to know see what was the most common position among my connections, so I made a word cloud.
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Recap & Reflection &
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We live in an age of technology where so much of our data is being collected. Using my own LinkedIn data, I discovered several things:
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My top ten connections are the people with whom I've messaged most and have also known the longest on LinkedIn.
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My LinkedIn connections work at a diverse group of companies.
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Since March 2022, my connections have grown to 855, with the most significant peak on November 13, 2022 when 81 others requested a connection with me.
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Most of my connections are other Data Analysts (76) and the next leading job position is that of Technical Recruiter (17).
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Reflecting on this information has given me the following ideas.​
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While it's lovely to have a few strong connections with whom I correspond regularly, it would be a good idea to be intentional about also strengthening other connections.
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Likewise, knowing a lot of other Data Analysts has its advantages. However, I also need to begin to broaden my connections to other job positions to have a healthy and diverse network.
This data visualization is available to view and explore in more detail: Carly's LinkedIn Insights.
Action!
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I thank you for reading and welcome your feedback! Please consider following me or connecting on LinkedIn at Carly Jocson. And keep me in mind for any remote positions as a data analyst!