大规模在线游戏网络用户行为研究

项目名称： 大规模在线游戏网络用户行为研究

项目编号： No.61502500

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 贾璐

作者单位： 中国农业大学

项目金额： 21万元

中文摘要： 在线游戏网络以其独有的游戏及社交影响力，已经成功的在世界范围内吸引了数亿用户，其在全球范围内的产业估值达到数百亿美元。和普通在线社交网络不同，以游戏为载体，游戏网络中的的用户关系是丰富而又独特的。本课题预期首先进行大规模多人在线游戏网络测量，为分析和挖掘游戏网络用户关系提供量化可靠性保证；其次针对游戏网络中特有的动态用户交互信息，改进传统复杂网络方法的不足，设计有效的游戏网络关系提取模型；最后，基于游戏网络用户关系挖掘，改进传统复杂网络关系预测方法的不足，设计适用于游戏网络的用户关系及比赛推荐算法。深刻理解游戏网络中的用户关系，从而为拥有用巨大用户基数，涵盖重要工业产值的游戏网络提供更精准的服务设计，具有十分重要的科学意义和实用价值。

中文关键词： 社会关系网络；社会网络分析；在线社交网络

英文摘要： 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 project, we focus on understanding social relationships in MOGs. We first carry out a large-scale measurement on user behaviors in MOGs. Then, 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 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.

英文关键词： Social relationship networks;Social network analysis;Online social networks