4.74 Is the New 6

I've owned a LinkedIn account for several years now, but I didn't flesh out the details until just last year.  As of the beginning of this week, I had 39 connections.  When I learned Tuesday that InMaps requires a minimum of 50 connections to function, the race was on.  I poured through the list of suggested connections, my Gmail contacts, my Facebook friends, and even scrolled through every name listed in my phonebook.  In order to get the 11 additional connections needed to use InMaps, I figured I needed to send at least 15 invitations (and ideally more like 20).  With this in mind, suddenly connection selection became a game.  I sent invitations to people I would have spent days (or even weeks) agonizing over whether I should make contact, like the Corporate Investigator I worked with this time last year.  Instead of worrying if he would remember me, I just hit the send button.  By the time I went to bed Tuesday night, I already had three notifications that people had accepted my request to connect.  When I woke up Wednesday, I had three more notifications.  At this point, I was halfway to my goal of 11 new connections, and the next couple hours felt like I watching a fundraising leader board as additional notifications pinged my phone.  It was exciting, and by 9am Wednesday morning, I had 51 new connections.  Mission accomplished.

Imagine my surprise when I logged into LinkedIn to set up InMaps, and discovered a new "Who's viewed your profile" page.  This tool shows profile views, the top location of viewers, viewer titles, and how many viewers found my profile using LinkedIn search.

While this tool is far less sophisticated than MicroStrategy or Google Analytics, it appears to be an attempt to share the same type of information with LinkedIn users.  If a person was actively using LinkedIn to generate leads, I can imagine this being quite valuable to track network progress.

After securing my 51st connection, I was excited to see what else I could learn about my network from InMaps.  I expected to see three distinct sub-graphs: Barnes & Noble, University of Arizona, and Arizona State University, alongside a small assortment of outliers.  However, when I loaded my map, the picture was a bit different.

I still had three distinct sub-networks, but they contained different information than I predicted.  I ended up labeling my three main network areas as current Barnes & Noble employees, former Barnes & Noble employees, and University of Arizona.  There is definitely some overlap between the two type of B&N connections, and one node with a significantly higher degree of centrality.  My most influential connectors are Danae, Julie, and Jason.  If I look outside the graph to consider why, it's easy to discern a pattern.  I direct reported to Danae and then Julie at B&N, for five of the last six years.  Danae works for a different company now, but she is the primary connector among current and former B&N employees.  And while Jason was never my boss, he has been a peer since 2011 and the person I would most likely identify as my mentor.  It makes sense that my connection with him influences my connections with other active employees in the company.

The absence of any real pattern relating to ASU surprised me, until I realized that my ASU connections are scattered.  In other words, I know each of them, but they apparently don't know each other so when represented graphically, they make up a large segment of the outliers group.  

As I waited for connection notifications yesterday, it occurred to me that all this talk about network science reminded me of the Six Degrees of Kevin Bacon game.  I had always considered Six Degrees as something of a pop culture phenomenon, but I learned that it is actually based in network science from the 1960s.  Psychologist Stanley Milgram conducted an experiment that resulted in the Six Degrees of Separation theory, "according to which everyone and everything is six or fewer steps away, by way of introduction, from any other person in the world" (Jean, 2013, p. 1).  While network science wasn't a term used at that time, it appears this experiment served as an early project in that field.

Interestingly, I came across a New York Times article from 2011, which reported the results of recent Facebook research and posits that "the average number of acquaintances separating any two people in the world was not six but 4.74" (Markoff & Sengupta, 2011, p. 1).  If 6 sounded like a small number, 4.74 is shockingly small.  I shared this information with several friends and coworkers yesterday, mostly for the purpose of gauging their reactions. Their response was similar to mine: after years of accepting 6 as the magic number, the thought of 4.74 "hops" between any two Facebook-using humans sounds impossibly small and for those less comfortable with technology, even a bit scary.

Once I got over my initial shock about how small the world really is, this knowledge actually made me more comfortable about my Tuesday night LinkedIn connection campaign.  My concern about the Corporate Investigator not remembering that I had been part of a case resolution in 2013?  Irrelevant.  My Regional Loss Prevention Director was already connected to the Investigator, and I was already connected to the RLPD so it was a short hop, even if he had forgotten about that case from last year.  For that matter, now that I know that a mere 4.74 degrees separates me from anyone else I may want to connect with, I will be less distressed about forging new connections in the future.  If I don't know someone but want to, chances are it's a short distance to travel to get there considering my growing network.

References

Jean.  (2013, September 2).  Six degrees of Kevin Bacon: a webinar on graph visualization (and movies).  Retrieved from http://linkurio.us/6-degrees-of-kevin-bacon-a-webinar-on-graph-visualization-and-movies/

Markoff, J., & Sengupta, S.  (2011, November 21).  Separating you and me?  4.74 degrees.  New York Times.  Retrieved from http://www.nytimes.com/2011/11/22/technology/between-you-and-me-4-74-degrees.html?_r=0 

Ram, S.  (2014).  Network properties [PDF].  Available from http://courses.eller.arizona.edu/mis/587/ram/Lecture13/