Müller, S, Frey, S, Kapadia, M et al. (5 more authors) (2015) HEAPCRAFT: Quantifying and Predicting Collaboration in Minecraft. In: Jhala, A and Sturtevant, N, (eds.) Proceedings, The Eleventh AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE 2015). Eleventh Annual AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 14-18 Nov 2015, University of California Santa Cruz. AAAI Press , pp. 156-162. ISBN 978-1-57735-740-7
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 or recording gameplay. We collected over 3451 playerhours 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.
Metadata
Item Type: | Proceedings Paper |
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Copyright, Publisher and Additional Information: | (c) 2015, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. This is an author produced version of a paper published in Proceedings of the Eleventh Artificial Intelligence and Interactive Digital Entertainment International Conference (AIIDE 2015). Uploaded in accordance with the publisher's self-archiving policy |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Aug 2015 15:22 |
Last Modified: | 15 Jan 2018 23:39 |
Published Version: | http://www.aaai.org/ocs/index.php/AIIDE/AIIDE15/pa... |
Status: | Published |
Publisher: | AAAI Press |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:89130 |