Understanding and recommending play relationships in online social gaming

et al. 2014

IEEE Internet Comput.

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Abstract-For many networked games, such as the Defense of the Ancients and StarCraft series, the unofficial leagues created by players themselves greatly enhance user-experience, and extend the success of each game. Understanding the social structure that players of these games implicitly form helps to create innovative gaming services to the benefit of both players and game operators. But how to extract and analyse the implicit social structure? We address this question by first proposing a formalism consisting of various ways to map interaction to social structure, and apply this to real-world data collected from three different game genres. We analyse the implications of these mappings for in-game and gaming-related services, ranging from network and socially-aware matchmaking of players, to an investigation of social network robustness against player departure.

Section: Introductionmentioning

confidence: 59%

“…In contrast, a socially-aware matchmaking service assigns players to matches, trying to ensure that players in the same social, rather than latency-based, cluster play together. We revisit the example of a sociallyaware matchmaking service presented in [4], by also considering network latency.…”

Section: A Socially and Network-aware Matchmakingmentioning

confidence: 99%

Analyzing Implicit Social Networks in Multiplayer Online Games

losup

Bovenkamp

et al. 2014

IEEE Internet Comput.

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“…Table II shows the statistics, including the mean and standard deviation, of the daily injection rate in different days of a week. The weekend pattern has been observed in other UGC sharing sites, such as YouTube-Live , and Daum (a Koren UGC site) [Cha et al 2009] and a DotA gaming site [van de Bovenkamp et al 2013].…”

Section: Gamecast Injectionmentioning

confidence: 68%

When Game Becomes Life

Jia

ACM Trans. Multimedia Comput. Commun. Appl.

Epema

et al. 2016

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Online gaming franchises such as World of Tanks, Defense of the Ancients, and StarCraft have attracted hundreds of millions of users who, apart from playing the game, also socialize with each other through gaming and viewing gamecasts. As a form of User Generated Content (UGC), gamecasts play an important role in user entertainment and gamer education. They deserve the attention of both industrial partners and the academic communities, corresponding to the large amount of revenue involved and the interesting research problems associated as UGC sites and social networks. Although previous work has put much effort in analyzing general UGC sites such as YouTube, relatively little is known about the gamecast sharing sites. In this work, we provide the first comprehensive study of gamecast sharing sites, including commercial streaming-based sites such as Amazon's Twitch.tv and community-maintained replay-based sites such as WoTreplays. We collect and share a novel dataset on WoTreplays that includes more than 380 thousand game replays, shared by over 60 thousand creators with over 1.9 million gamers. Together with an earlier published dataset on Twitch.tv, we investigate basic characteristics of gamecast sharing sites, and we analyze the activities of their creators and spectators. Among our results, we find that (i) WoTreplays and Twitch.tv are both fast-consumed repositories, with millions of gamecasts being uploaded, viewed, and soon forgotten; (ii) both the gamecasts and the creators exhibit highly skewed popularities, with a significant heavy tail phenomenon; and (iii) the upload and the download preference of creators and spectators are different: while the creators emphasize their individual skills, the spectators appreciate team-wise tactics. Our findings provide important knowledge for infrastructure and service improvement, for example, in the design of proper resource allocation mechanisms that consider future gamecasting, and in the tuning of incentive policies that further help player retention.

“…We believe this is because it has the largest match scale: most matches in World of Tanks are 15v15-player, whereas matches in DotA and StarCraft II are 5v5-player and (mostly) 1v1-player. A more detailed description of the datasets can be found in our previous work [van de Bovenkamp et al 2013] and [Iosup et al 2014].…”

Section: Datasets Of Mogsmentioning

confidence: 99%

“…Our previous work [van de Bovenkamp et al 2013] and [Iosup et al 2014] propose graph models to analyze social relationships in MOGs, but they lack a thorough study of the impact of mapping functions and thresholds on the characteristics of the resulting graphs.…”

Section: Socializing By Gaming: Revealing Social Relationships In Mulmentioning

confidence: 99%

Socializing by Gaming

Jia

ACM Trans. Knowl. Discov. Data

Bovenkamp

et al. 2015

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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 10 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.