Abstract
The design of software is often a process of intuition, guessing, and luck. It does not have to be. We present association mapping (AM), a novel take on social-network analysis that removes the human-centric biases of network analysis. To show the usefulness of this approach, we deploy AM on a board game and compare it to the digital version of that same board game. Overall, we show just how much less central humans are in thedigital version of the board game and how that loss of centrality influenced the humans themselves. After discussing the reasoning behind the method, how to do AM, and what the data mean, we discuss how to deploy AM for design and different paths AM could develop.
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Notes
- 1.
It is important to note here that NodeXL is not a requirement and that R or any other software that accepts these types of data are just as useful.
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LaLone, N. (2021). Gameplay as Network: Understanding the Consequences of Automation on Play and Use. In: Fang, X. (eds) HCI in Games: Experience Design and Game Mechanics. HCII 2021. Lecture Notes in Computer Science(), vol 12789. Springer, Cham. https://doi.org/10.1007/978-3-030-77277-2_23
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