Abstract
Analyzing the user behavior of multiplayer online games can help understand the sociality and characteristics of players in the virtual world. The primary task is to characterize the game life and its evolution within the game. We propose a novel network-based representation, EvolutionLine Graph, that illustrates the evolving behavior of massive game players as a sequence of time-oriented transitions among various status. We design and implement a novel visual analytics system, GameLifeVis, that supports the visualization, exploration, and analysis of multi-level user behaviors in an integrated visual interface. We exemplify the efficiency of our approach with case studies on a multi-faceted dataset collected within a popular online game (15 million players) in 18 months.
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References
Riedl, M.O., Zook, A.: AI for game production. In: IEEE Conference on Computational Intelligence in Games, CIG 2013, pp. 1–8. IEEE (2013)
Wang, F.Y.: Social computing: fundamentals and applications. In: IEEE International Conference on Intelligence and Security Informatics, ISI 2008, pp. xxxv–xxxviii. IEEE (2008)
Bartle, R.: Hearts, clubs, diamonds, spades: players who suit muds. J. MUD Res. 1(1), 19 (1996)
Bainbridge, W.S.: The scientific research potential of virtual world. Science 317, 472–476 (2007)
Matsumoto, Y., Thawonmas, R.: MMOG player classification using hidden Markov models. In: Rauterberg, M. (ed.) ICEC 2004. LNCS, vol. 3166, pp. 429–434. Springer, Heidelberg (2004)
Natkin, S., Yan, C.: User model in multiplayer mixed reality entertainment applications. In: Advances in Computer Entertainment Technology, p. 74. ACM (2006)
Wang, S.T., Yang, J.C., S.Y., C., Kuo, W.C.: The clusters of gaming behavior in MMORPG: a case study in Taiwan. In: IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012, pp. 263–266 (2012)
Bauckhage, C., Drachen, A., Sifa, R.: Clustering game behavior data. IEEE Trans. Comput. Intell. AI Games 7(3), 266–278 (2015)
Cox, A., Stasko, J.: SportVis: discovering meaning in sports statistics through information visualization. In: IEEE Symposium on Information Visualization, pp. 115–116. IEEE (2006)
Beck, F., Burch, M., Weiskopf, D.: Visual comparison of time-varying athletes’ performance. In: Proceedings of the 1st Workshop on Sports Data Visualization (2013)
Correa, C.D., Crnovrsanin, T., Muelder, C., Shen, Z., Armstrong, R., Shearer, J., Ma, K.: Cell phone mini challenge award: intuitive social network graphs visual analytics of cell phone data using mobivis and ontovis. In: IEEE Conference on Visual Analytics Science and Technology, VAST 2008, pp. 211–212. IEEE (2008)
Shi, C., Wu, Y., Liu, S., Zhou, H., Qu, H.: Loyaltracker: visualizing loyalty dynamics in search engines. IEEE Trans. Vis. Comput. Graph. 20(12), 1733–1742 (2014)
Wu, Y., Liu, S., Yan, K., Liu, M., Wu, F.: Opinionflow: visual analysis of opinion diffusion on social media. IEEE Trans. Vis. Comput. Graph. 20, 1763–1772 (2014)
Agrawal, S., Sravanthi, K., Vadapalli, S., Karlapalem, K.: Vast 2009 traffic mini challenge: intuitive analytic information presentation. In: IEEE Conference on Visual Analytics Science and Technology, VAST 2009, pp. 271–272. IEEE (2009)
Zhang, J., Chen, C., Vogeley, M.S., Pan, D., Thakar, A., Raddick, J.: SDSS log viewer: visual exploratory analysis of large-volume SQL log data. Proc. Visual. Data Anal. 8294, 1–13 (2012)
Wongsuphasawat, K., Gotz, D.: Exploring flow, factors, and outcomes of temporal event sequences with the outflow visualization. IEEE Trans. Visual. Comput. Graphics 18(12), 2659–2668 (2012)
Song, L., Kolar, M., Xing, E.P.: Time-varying dynamic Bayesian networks. In: Bengio, Y., Schuurmans, D., Lafferty, J., Williams, C., Culotta, A. (eds.) Advances in Neural Information Processing Systems, vol. 22, pp. 1732–1740. Curran Associates Inc., Red Hook (2009)
Kim, G., Xing, E.: Reconstructing storyline graphs for image recommendation from web community photos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2014, pp. 3882–3889 (2014)
Kosara, R., Bendix, F., Hauser, H.: Parallel sets: interactive exploration and visual analysis of categorical data. IEEE Trans. Visual. Comput. Graphics 12(4), 558–568 (2006)
Acknowledgements
This work is supported by NSFC (61232012, 61422211, 61303141), Zhejiang NSFC (Y12F020172), and the Fundamental Research Funds for the Central Universities
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Liu, Z. et al. (2016). Visual Exploration of Virtual Lives in Multiplayer Online Games. In: El Rhalibi, A., Tian, F., Pan, Z., Liu, B. (eds) E-Learning and Games. Edutainment 2016. Lecture Notes in Computer Science(), vol 9654. Springer, Cham. https://doi.org/10.1007/978-3-319-40259-8_1
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DOI: https://doi.org/10.1007/978-3-319-40259-8_1
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