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1 ASCI, 2010 – Analysis of BBO Fans Social Networks Analysis of BBO Fans, an Online Social Gaming Community Alexandru Iosup Parallel and Distributed Systems.

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Presentation on theme: "1 ASCI, 2010 – Analysis of BBO Fans Social Networks Analysis of BBO Fans, an Online Social Gaming Community Alexandru Iosup Parallel and Distributed Systems."— Presentation transcript:

1 1 ASCI, 2010 – Analysis of BBO Fans Social Networks Analysis of BBO Fans, an Online Social Gaming Community Alexandru Iosup Parallel and Distributed Systems Group Delft University of Technology Vlad Posea, Mihaela Balint, Alexandru Dimitriu Politehnica University of Bucharest, Romania

2 ASCI, 2010 – Analysis of BBO Fans 2 What’s in a name? 1.Virtual world Explore, do, learn, socialize, compete + 2.Content Graphics, maps, puzzles, quests, culture + 3.Game analytics Player stats and relationships Massively Social Gaming (online) games with massive numbers of players (100K+), for which social interaction helps the gaming experience

3 ASCI, 2010 – Analysis of BBO Fans 3 MSGs are a Popular, Growing Market 25,000,000 subscribed players (from 150,000,000+ active) Over 10,000 MSGs in operation Market size 7,500,000,000$/year Sources: MMOGChart, own research.Sources: ESA, MPAA, RIAA.

4 ASCI, 2010 – Analysis of BBO Fans 4 Social Networks: Buzzword? Science? Social Network=undirected graph, relationship=edge Community=sub-graph, density of edges between its nodes higher than density of edges outside sub-graph

5 ASCI, 2010 – Analysis of BBO Fans 5 FarmVille, a Massively Social Game Key advantage over market: Use [Social Network] analysis to improve gameplay experience Zynga CTO Sources: CNN, Zynga, 2010. Source: InsideSocialGames.com

6 ASCI, 2010 – Analysis of BBO Fans 6 Agenda 1.Background on Massively Social Gaming 2.Bridge, the Running Example 3.Research Question 4.Addressing the Research Question 5.Conclusion

7 ASCI, 2010 – Analysis of BBO Fans 7 Bridge, A Traditional Team Card Game Bridge as traditional card game 2 pairs (4 players) play hands (bidding + play) Duplicate bridge: same hand at every table, eliminates luck Only team game at last World Mind Sport Games, Beijing, 2008 Bridge as special use case of social networks Complex agreements between partners (like a social partnership) A good pair forms in a very long period of time (like a social …) How to find a good partner?

8 ASCI, 2010 – Analysis of BBO Fans 8 BBO (Fans): Massively Social Gaming Bridge Base Online (BBO) http://www.bridgebase.comhttp://www.bridgebase.com Largest online bridge platform, free to play 1M active players, also attracts many professional players Friends and enemies, filtering by skill and nationality No advanced social networking features, e.g., No Friends-of-Friends BBO Fans http://www.bbofans.com/http://www.bbofans.com/ Uses BBO for actual gameplay Better social network facilities Community tools: awards, ranking, rated tournaments, etc.

9 ASCI, 2010 – Analysis of BBO Fans 9 Research Question: Characteristics of an Online Bridge Community? Study the activity and soc.net. characteristics of BBOFans Why is this interesting? Unique type of social network? (new knowledge) Unique type of social gaming network? (new knowledge) Use results to develop new services (matchmaking, rating) Use results to improve online game operations (player retention) “Real-world” applications: other social network results applied in economics; adversarial settings good for management and psychology studies; etc.

10 ASCI, 2010 – Analysis of BBO Fans 10 Agenda 1.Background on Massively Social Gaming 2.Bridge, the Running Example 3.Research Question 4.Addressing the Research Question Method Data Activity Levels Social Network Properties 5.Conclusion

11 ASCI, 2010 – Analysis of BBO Fans 11 Analysis of BBOFans Method 1.Gather data from BBO logs 2.Analyze activity levels 3.Transform the play data in a G=(V,E), V=set of players, E=set of social relations. Social relations = play-as-pair relationships Use a parameter p (number of hands played together) to establish when two players have a social relation 4.Analyze properties of graph G Traditional soc.net. analysis, e.g., clustering coefficient Player type analysis

12 ASCI, 2010 – Analysis of BBO Fans 12 Analysis of BBOFans 1. Gathered Data Domain-specific web crawler BBO + BBO Fans data Vlad Posea, Mihaela Balint, Alexandru Dimitriu, and Alexandru Iosup, An Analysis of the BBO Fans online social gaming community, RoEduNet International Conference (RoEduNet), 2010 9th.

13 ASCI, 2010 – Analysis of BBO Fans 13 Large (~10K) online comms. can coordinate Analysis of BBOFans 2. Activity Levels: Popular, Synch’d. Interaction BBOFans-BBO Coordinated large-scale social group BBOFans ~ FaceBook Top-1,000 app (DAU) BBO/BBOFans ~ Top-500

14 ASCI, 2010 – Analysis of BBO Fans 14 Weakly connected community, weaker than FB, YouTube Many small communities, one large component, Fans+ Analysis of BBOFans 3/4. Properties of Social Graph (1) Clustering Coeff. Mean Comm. Size Number of Communities

15 ASCI, 2010 – Analysis of BBO Fans 15 Player Types Community Builder plays many hands with many other players Community Member plays mostly with a few community members Faithful Player 1-2 stable partners Random Player no stable partner (Memory jog: Creating a bridge relationship takes longer than creating a relationship in FaceBook, Orkut, …) Analysis of BBOFans 3/4. Properties of Social Graph (2) Mihaela Balint, Vlad Posea, Alexandru Dimitriu, and Alexandru Iosup, User Behavior, Social Networking, and Playing Style in Online and Face to Face Bridge Communities, NetGames 2010.

16 ASCI, 2010 – Analysis of BBO Fans 16 Agenda 1.Background on Massively Social Gaming 2.Bridge, the Running Example 3.Research Question 4.Addressing the Research Question 5.Conclusion

17 ASCI, 2010 – Analysis of BBO Fans 17 Current Technology The Future Scalability, efficiency Happy players Million-users, multi-bn. market Content, World Sim, Analytics Massively Social Gaming Complete game mechanics Basic social network tools Makes players unhappy Many starters quit Our Vision Social Network Analysis + Applications = BridgeHelper Ongoing Work More analysis Ranking Matchmaking

18 ASCI, 2010 – Analysis of BBO Fans 18 Thank you for your attention! Questions? Suggestions? Observations? Alexandru Iosup A.Iosup@tudelft.nl http://www.pds.ewi.tudelft.nl/~iosup/ (or google “iosup”) Parallel and Distributed Systems Group Delft University of Technology A.Iosup@tudelft.nl http://www.pds.ewi.tudelft.nl/~iosup/ - http://www.st.ewi.tudelft.nl/~iosup/research_gaming.htmlhttp://www.st.ewi.tudelft.nl/~iosup/research_gaming.html - http://BridgeHelper.org (soon)http://BridgeHelper.org More Info:

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