Many of the hundreds of millions Massively Multiplayer Online Games (MMOGs) players are also involved in the social networks built around the MMOGs they play. Through these networks, these players exchange game news, advice, and expertise, and expect in return support such as player reports and clan statistics. Thus, the MMOG social networks need to collect and analyze MMOG data, in a process of continuous MMOG analytics. In this chapter we investigate the use of CAMEO, an architecture for Continuous Analytics for Massively multiplayEr Online games on cloud resources, to support the analytics part of MMOG social networks. We present the design and implementation of CAMEO, with a focus on the cloud-related benefits and challenges. We also use CAMEO to do continuous analytics on a real MMOG community of over 5,000,000 players, thus performing the largest study of an online community, to-date. © 2011 Springer-Verlag Berlin Heidelberg.
|Title of host publication||Next Generation Data Technologies for Collective Computational Intelligence|
|Number of pages||26|
|Publication status||Published - 2011|
|Name||Studies in Computational Intelligence|