I am fascinated by LinkedIn’s new inMaps feature.
I’ve mapped my LinkedIn network using inMaps, and have a thick curiosity about the characteristics of the people in my network that link across my different affinities. What is special about them? The vast majority of my network do not link beyond a single affinity. But a few do.
Some connections make perfect sense, such as a business professor from one school connecting with students and professors at another school. Connections across two affinities are not unusual either. The people I connect with are likely to have more than one thing in common with me, so they naturally know my connections in those other circles as well. But there are a few that have multiple common groups with me. This makes me wonder what the map would look like in different contexts. In all of San Francisco, what is the threshold for common groups? What about in New York? St. Louis? What would a map of common networks criss-crossing the United States look like? What about one spanning the globe? Do these people with diversely common networks share characteristics that become more salient as we zoom out? Or does the commonality depend completely on the ego’s perspective? How does race, age, gender, nationality, education, or profession affect the makeup of diversely common connections?
Looking at my husband’s network, I find a lot more diversely common connections.
While he has many more connections than me, his networks are much more integrated than mine.
What does this say about his network? Are they generally more social than my connections? Do his connections have a lot more in common than my own? What would an extended map showing the connections of his and my connections look like? Would mine expand broadly like a puddle and his condense into a thick cloud?
It is wonderful to see the variety of connection types captured in our networks. Knowing these people personally, I can begin to guess the logic behind their position in my network. I am eager to understand the science behind these networks and put order to the chaos.
