After all the effort of building a dataset for The Reliants Project, it’s been great the reap the rewards with countless ways to explore and visualise the data. I’ve decided to focus first on the reliants, my closest relationships.
To give readers a sense of the breadth of the group categorised as reliants, here are some reference points. They include family members I’ve known since birth, others I’ve built relationships with spanning 25+ years, as well as people I’ve gotten to know within the last year. I met an equal number through direct introductions and public events and there are even two that I met serendipitously. They are overwhelmingly male, but very diverse in terms of nationality and ethnicity. Their ages span from mid-twenties to retired, though the majority are 25-45. Almost all of them have moved internationally and have lived in the same city as me at some point, though there are a couple of exceptions. Roughly half of them are married and/or have children, however few had reached this life stage when I met them. Beyond family (2 people), two pairs have relationships with each other that pre-date me. Even though all my reliants have been incredibly important to me at various stages of my life, there has been a 66% turnover in my reliants over the last 15 years.
One of the first things that struck me after creating the visual above is the consistency of node quantity overall (11-15) and the balance of nodes between locations, which is evenly distributed (4-7). Unsurprisingly, this closely reflects the Dunbar “rule of three“. It’s as if my brain makes space for a certain number of very close relationships and adjusts as life events and stage changes occur. Also, my network has become increasingly interconnected over time, as I get the opportunity to introduce reliants to each other in an effort to make those relationships more resilient. I suspect that trend will play out as my time in London lengthens.
In the series of graphs below, I take each of the reliants depicted in 2015 (above) and visualise them in the context of our shared network. The sequence is based on the order in which I met each of them. You can see how 1, 6, and 13 straddle locations, either between US and Hong Kong or Hong Kong and London. You can also see how close the relationships are between 7 and 8 as well as 9 and 10 because of the consistency of the network visuals and their position within them. It’s also easy to spot the people who have never lived in the same city as I have, such as 14. All of the graphs of my new London reliants look very similar to 15. The combination is a lovely fireworks display!
One of the many paths that I would like to explore is qualifying both the nodes and edges (reliants and our relationships with each other). While there are many ways to assess the nodes (such as the Social Style Model I used in my questionnaire), there are few ways to assess the edges. Recently I had the pleasure of meeting someone very familiar with the Relational Proximity Framework, which acknowledges the multiplexity of relationships and seeks to assess them using 5 domains: power, information, communication, purpose and story. Hoping that I can find an elegant way to display those dimensions and add richness to the data visualisations and insights that can be generated from them.
As always, would love any suggestions!