HeapCraft: Quantifying and Predicting Collaboration in Minecraft

Authors

  • Stephan Müller ETH Zurich
  • Seth Frey Disney Research Zurich
  • Mubbasir Kapadia Rutgers University
  • Severin Klingler ETH Zurich
  • Richard Mann ETH Zurich and University of Leeds
  • Barbara Solenthaler ETH Zurich
  • Robert Sumner Disney Research Zurich and ETH Zurich
  • Markus Gross Disney Research Zurich and ETH Zurich

DOI:

https://doi.org/10.1609/aiide.v11i1.12807

Abstract

We present Heapcraft: an open-source suite of tools for monitoring and improving collaboration in Minecraft. At the core of our system is a data collection and analysis framework for recording gameplay. We collected over 3451 player-hours of game behavior from 908 different players, and performed a general study of online collaboration. To make our game analytics easily accessible, we developed interactive information visualization tools and an analysis framework for players, administrators, and researchers to explore graphs, maps and timelines of live server activity. As part of our research, we introduce the collaboration index, a metric which allows server administrators and researchers to quantify, predict, and improve collaboration on Minecraft servers. Our analysis reveals several possible predictors of collaboration which can be used to improve collaboration on Minecraft servers. Heapcraft is designed to be general, and has the potential to be used for other shared online virtual worlds.

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Published

2021-06-24

How to Cite

Müller, S., Frey, S., Kapadia, M., Klingler, S., Mann, R., Solenthaler, B., Sumner, R., & Gross, M. (2021). HeapCraft: Quantifying and Predicting Collaboration in Minecraft. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 11(1), 156-162. https://doi.org/10.1609/aiide.v11i1.12807