Abstract
Multiplayer Online Games (MOGs) like Defense of the Ancients and StarCraft II have attracted hundreds of millions of users who communicate, interact, and socialize with each other through gaming. In MOGs, rich social relationships emerge and can be used to improve gaming services such as match recommendation and game population retention, which are important for the user experience and the commercial value of the companies who run these MOGs. In this work, we focus on understanding social relationships in MOGs. We propose a graph model that is able to capture social relationships of a variety of types and strengths. We apply our model to real-world data collected from three MOGs that contain in total over ten years of behavioral history for millions of players and matches. We compare social relationships in MOGs across different game genres and with regular online social networks like Facebook. Taking match recommendation as an example application of our model, we propose SAMRA, a Socially Aware Match Recommendation Algorithm that takes social relationships into account. We show that our model not only improves the precision of traditional link prediction approaches, but also potentially helps players enjoy games to a higher extent.
- L. A. Adamic and E. Adar. 2001. Friends and neighbors on the web. Soc. Netw. 25, 3, 211--230.Google ScholarCross Ref
- C. S. Ang. 2011. Interaction networks and patterns of guild community in massively multiplayer online games. Soc. Netw. Anal. Min. 1, 4, 341--353.Google ScholarCross Ref
- M. Balint, V. Posea, A. Dimitriu, and A. Iosup. 2011. An analysis of social gaming networks in online and face to face bridge communities. In ACM Workshop on Large-scale System and Application Performance (LSAP’11). 35--42. Google ScholarDigital Library
- R. Sulo Caceres and T. Berger-Wolf. 2013. Temporal Networks. Springer, Berlin, 25--94 pages.Google Scholar
- N. Caplar, M. Suznjevic, and M. Matijasevic. 2013. Analysis of players in-game performance vs rating: Case study of Heroes of Newerth. In Proceedings of Foundations of Digital Games Conference. 237--244.Google Scholar
- D. Cartwright and F. Harary. 1956. Structure balance: A generalization of Heider’s theory. Psychol. Rev. 63, 5, 277--293.Google ScholarCross Ref
- M. De Choudhury, W. A. Mason, J. M. Hofman, and D. J. Watts. 2010. Inferring relevant social networks from interpersonal communication. In Proceeding of the 12th International World Wide Web Conference (WWW’10). 301--310. Google ScholarDigital Library
- A. Clauset, C. R. Shalizi, and M. E. J. Newman. 2009. Power-law distributions in empirical data. SIAM Rev. 51, 4, 661--703. Google ScholarDigital Library
- S. Garg, T. Gupta, N. Carlsson, and A. Mahanti. 2009. Evolution of an online social aggregation network: an empirical study. In Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference (IMC’09). 315--321. Google ScholarDigital Library
- F. Heider. 1944. Social perception and phenomenal relations. Psychol. Rev. 51, 6, 358--374.Google ScholarCross Ref
- F. Heider. 1946. Attitudes and cognitive organization. J. Psychol. 21, 1, 107--112.Google ScholarCross Ref
- H. Hu and X. Wang. 2009. Evolution of a large online social network. Phys. Lett. A 373, 12--13, 1105--1110.Google ScholarCross Ref
- A. Iosup, R. van de Bovenkamp, S. Shen, A. L. Jia, and F. Kuipers. 2014. An analysis of implicit social networks in multiplayer online games. IEEE Internet Computing 18, 3, 36--44.Google ScholarCross Ref
- J. Jiang, C. Wilson, X. Wang, W. Sha, P. Huang, Y. Dai, and B. Y. Zhao. 2013. Understanding latent interactions in online social networks. ACM Trans. Web (TWEB) 7, 4, 18--39. Google ScholarDigital Library
- S. R. Kairam, D. J. Wang, and J. Leskovex. 2012. The life and death of online groups: Predicting group growth and longevity. In Proceedings of the 5th ACM International Conference on Web Search and Data Mining (WSDM’12). 673--682. Google ScholarDigital Library
- L. Katz. 1953. A new status index derived from sociametric analysis. Psychometrika 18, 1, 39--43.Google ScholarCross Ref
- B. Kirman and S. Lawson. 2009. Hardcore classification: Identifying play styles in social games using network analysis. In Proceedings of the International Conference on Entertainment Computing (ICEC’09). 246--251. Google ScholarDigital Library
- G. Krings, M. Karsai, S. Bernharsson, V. D. Blondel, and J. Saramaki. 2012. Effects of time window size and placement on the structure of aggregated networks. EPJ Data Sci. 1, 4, 1--19.Google ScholarCross Ref
- J. Leskovec, J. Kleinberg, and C. Faloutsos. 2005. Graphs over time: Densification laws, shrinking diameters and possible explanations. In Proceeding of the 12th Int. World Wide Web Conference (WWW’05). 177--187. Google ScholarDigital Library
- D. Liben-Nowel and J. Kleinberg. 2003. The link prediction problem for social networks. In Proceeding of the 12th International Conference on Information and Knowledge Management (CIKM’03). 556--559. Google ScholarDigital Library
- X. Liu, Q. He, Y. Tian, W. Lee, J. McPherson, and J. Han. 2012. Event-based social networks: Linking the online and offline social worlds. In Proceeding of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’12). 1032--1040. Google ScholarDigital Library
- J. McGonigal. 2011. Reality is Broken: Why Games Make us Better and How They Can Change the World. Jonathan Cape, London, 1--400. Google ScholarDigital Library
- S. Merritt and A. Clauset. 2013. Social network dynamics in a massive online game: Network turnover, non-densification, and team engagement in halo reach. In Proceeding of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) Workshop on Mining and Learning with Graphs (MLG). 1--8.Google Scholar
- S. Milgram. 1967. The small world problem. Psych. Today 1, 1, 61--67.Google Scholar
- A. Mislove, M. Marcon, K. P. Gummadi, P. Druschel, and B. Bhattacharjee. 2007. Measurement and analysis of online social networks. In Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement Conference (IMC’07). 29--42. Google ScholarDigital Library
- M. E. J. Newman. 2003. The structure and function of complex networks. SIAM Rev. 45, 2, 167--256.Google ScholarDigital Library
- V. Posea, M. Balint, A. Dimitriu, and A. Iosup. 2010. An analysis of the BBO fans online social gaming community. In Proceedings of the 9th RoEduNet International Conference (RoEduNet’10). 35--42.Google Scholar
- B. Ribeiro, N. Perra, and A. Baronchelli. 2013. Quantifying the effect of temporal resolution on time-varying networks. Sci. Rep. 3, 3006, 1--5.Google Scholar
- J. L. Rodgers and W. A. Nicewander. 1988. Thirteen ways to look at the correlation coefficient. Am. Stat. 42, 1, 59--66.Google ScholarCross Ref
- H. H. Song, T. W. Cho, V. Dave, Y. Zhang, and L. Qiu. 2009. Scalable proximity estimation and link prediction in online social networks. In Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference (IMC’09). 322--335. Google ScholarDigital Library
- M. Szell and S.Thurner. 2012. Social dynamics in a large-scale online game. Adv. Complex Syst. 15, 6, 167--256.Google ScholarCross Ref
- R. van de Bovenkamp, S. Shen, A. Iosup, and F. A. Kuipers. 2013. Understanding and recommending play relationships in online social gaming. In the 5th International Conference on Communication Systems and Networks (COMSNETS’13). 1--10.Google Scholar
- B. Viswanath, A. Mislove, M. Cha, and K. P. Gummadi. 2009. On the evolution of user interaction in Facebook. In Proceedings of the 2nd ACM SIGCOMM Workshop on Online Social Networks (WOSN’09). 37--42. Google ScholarDigital Library
- D. J. Watts and S. H. Strogatz1. 1998. Collective dynamics of small-world networks. Nature 393, 6684, 440--442.Google Scholar
- C. Wilson, B. Boe, A. Sala, K. P. N. Puttaswamy, and B. Y. Zhao. 2009. User interactions in social networks and their implications. In Proceedings of the 4th ACM European Conference on Computer Systems (EuroSys’09). 205--218. Google ScholarDigital Library
- R. Xiang, J. Neville, and M. Rogati. 2010. Modeling relationship strength in onlince social networks. In Proceeding of the 19th International World Wide Web Conference (WWW’10). 981--990. Google ScholarDigital Library
Index Terms
Socializing by Gaming: Revealing Social Relationships in Multiplayer Online Games
Recommendations
Socializing in mobile gaming
DIMEA '08: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and ArtsCurrently the most prevalent format for mobile gaming is the single-player variety, where users interact with the game's artificial intelligence within a number of genres such as sports, action, racing, and puzzle games, etc. The users install the game ...
The social side of gaming: a study of interaction patterns in a massively multiplayer online game
CSCW '04: Proceedings of the 2004 ACM conference on Computer supported cooperative workPlaying computer games has become a social experience. Hundreds of thousands of players interact in massively multiplayer online games (MMORPGs), a recent and successful genre descending from the pioneering multi-user dungeons (MUDs). These new games ...
Sociable killers: understanding social relationships in an online first-person shooter game
CSCW '11: Proceedings of the ACM 2011 conference on Computer supported cooperative workOnline video games can be seen as medium for the formation and maintenance of social relationships. In this paper, we explore what social relationships mean under the context of online First-Person Shooter (FPS) games, how these relationships influence ...
Comments