Networks are a way of looking at many things: communication between people, links between web sites, ownership of companies, transportation and supply chain connections, marketing strategies and biological systems. There is a growing interest in Network Science, the study of networks, and at Hyper Island we have planned and accredited a course as part of our Masters Programme in Digital Management. It will add a new lens through which to look at the links between technology and humans.
We won’t offer this module until next year as our calendars are already full with course deliveries but as is common in the way we do things, I wanted to start to plan and prototype a programme and get past students involved in shaping it to make it highly relevant as part of the MA.
This will take shape over the next few months. As with all our courses I start with describing the outcomes I want our learners to achieve. By the end of the course I want to make sure they are able to identify tools and techniques to analyse and explore networks, identify application areas for this thinking within a range if different industries and i their own work, design experiments to collect data and test ideas and discuss the dangers and ethical issues exposed in network thinking.
Our goal across the whole programme is to give managers and leaders a wide range of ways of looking at the world and problems they face and network thinking will complement models of business transformation, systems thinking, scenario planning, design thinking and many other lenses.
Creating a practical hands-on study is central to the Hyper Island philosophy of learning through making and exploring and we’ll use a range of different tools to explore. This will reinforce the tool agnostic approach from other modules where we encourage learners to experiment without becoming expert in a single tool.
We will need data sets to explore and an example I have chosen to start with will be the existing alumni network itself. I constructed a survey and asked all of the existing students and alumni to identify their connections within the group. This is called an Ego Network study as it is based on individuals describing their own connections.
One week ago we emailed and used social networks to encourage them to answer and over half the group did. This is a big enough representative sample although it might tend to over estimate the strength of connections. Almost 90% of the students are “connected to” within this data.
Cleaning the data was a big (and expected) part of this first project. We have a class from Asia and registered student names often differ from the names that students are known by. I reduced the problem by creating my survey in Jotform and used a lookup widget (like Google Suggests) to allow students to identify names with minimal typing. There were still many partial names and misspellings that required manual cleaning before I could start analysis. But, within a week, I have a network…
In part two of this article I’ll start the analysis and explore the language of networks and some of the questions to which I hope I can find answers.
If you’d like to to know more about this module or the course please get in touch.