Summary

The last decade has witnessed the rise of big data in game development as the increasing proliferation of Internet-enabled gaming devices has made it easier than ever before to collect large amounts of player-related data. At the same time, the emergence of new business models and the diversification of the player base have exposed a broader potential audience, which attaches great importance to being able to tailor game experiences to a wide range of preferences and skill levels. This, in turn, has led to a growing interest in data mining techniques, as they offer new opportunities for deriving actionable insights to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation. By now, data mining and analytics have become vital components of game development. The amount of work being done in this area nowadays makes this an ideal time to put together a book on this subject.

Data Analytics Applications in Gaming and Entertainment seeks to provide a cross section of current data analytics applications in game production. It is intended as a companion for practitioners, academic researchers, and students seeking knowledge on the latest practices in game data mining. The chapters have been chosen in such a way as to cover a wide range of topics and to provide readers with a glimpse at the variety of applications of data mining in gaming. A total of 25 authors from industry and academia have contributed 12 chapters covering topics such as player profiling, approaches for analyzing player communities and their social structures, matchmaking, churn prediction and customer lifetime value estimation, communication of analytical results, and visual approaches to game analytics. This book's perspectives and concepts will spark heightened interest in game analytics and foment innovative ideas that will advance the exciting field of online gaming and entertainment.

Choice Review

This edited collection of twelve articles, contributed by academic experts in the field, explains and rationalizes different implementations of data science, including data mining and analytics, in gaming and entertainment. Any game played on a digital platform generates enormous amounts of data about gameplay, player behavior, and player experience, which can have significant impact if correctly and coherently collected and analyzed. Topics include, for example, use of data analytics to optimize player options and experience in multiplayer online battle games; creation of data science models to predict player behavior; and parsing of player communications to extract player social relationships and identify key players. Other articles discuss best practices for communicating the results of data analytics to development teams, and for integrating such results into their workflow. The book does not present actual analytic methodology, but offers a practical guide to anyone seeking to understand the importance of this new trend in the design, implementation, and commercialization of games. The book includes many useful graphics; however they are all presented in black and white. The data visualizations presented are often referenced by color, and thus the lack of color printing is most unfortunate. Summing Up: Recommended. Upper-division undergraduates through faculty and professionals. Students enrolled in two-year technical programs. --Elena Bertozzi, Quinnipiac University