Data Analytics Applications in Gaming and Entertainment

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.

Autorentext

Günter Wallner is senior scientist at the University of Applied Arts Vienna. He holds a doctorate degree in natural sciences from the University of Applied Arts Vienna and a diploma degree in computer science from the Vienna University of Technology. His research interests span the fields of Games Research, Data Analytics, Information Visualization, and HCI. Günter's current research focuses on the analysis and visualization of game telemetry data to derive actionable insights for driving game design - a topic on which he has published numerous articles in international journals and conference proceedings, such as Computers & Graphics, Entertainment Computing, SIGCHI, CHIPLAY, FDG, and ACE. He also serves regularly on a number of program committees, mainly for gamerelated conferences.

Klappentext

Over the last decade big data and data mining has received growing interest and importance in game production to process and draw actionable insights from large volumes of player-related data in order to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation. This volume seeks to provide a comprehensive overview of data mining applications pertaining to various aspects of game production, including game analytics, games user research, and artificial intelligence. It covers topics such as player behavior analysis and profiling, retention analysis, visualization, as well as data-driven artificial intelligence and content generation.

Inhalt

Part 1 - Introduction to game data mining.

Part 2 - Data mining for games user research.

Part 3 - Data mining for game technology.

Part 4 - Visualization of large-scale game data.