瑞典数字媒体方向研究前沿及教学

发布时间:2014-12-12  阅读次数:2140
 瑞典数字媒体方向研究前沿及教学
Trends of Teaching and Research in Digital Creativity in Sweden
--- Collaborative Engagement for Game Player Data Analytics
Prof. Masayuki Nakajima
Department of Game Design, Faculty of Arts, Uppsala University

Bio: 
 Prof. Masayuki Nakajima, the Professor of Department of Game Design, Faculty of Arts, Uppsala University, Emeritus Professor of Tokyo Institute of Technology and Visiting Professor of Kanagawa Institute of Technology. He received Dr. Eng. degree from the Tokyo Institute of Technology, Tokyo, Japan in 1975 and had been Professor at the Department of Computer Science, Tokyo Institute of Technology during 1994-2012 March. He was Professor of Gotland University from April, 2012. Now, he is Professor of Uppsala University from 2013 July.
URL: http://www.uunaka.org/uu/
http://convergentmedialab.com/
 
Abstract:
 Game analysis is the application of analysis to game development and research. The goal is to support decision making, at operational, tactical and strategic levels and within all levels of an organization - design, art, programming, marketing, user research, etc. It has gained a tremendous amount of attention in game development and game research in recent years. It is driven by the need to gain better knowledge about the players. This need has been emphasized with the rapid emergence of social online games and the Free-to-Play business model, which heavily inspired by web- and mobile analysis, relies on analysis of comprehensive user behavior data to drive revenue. Outside of the online game sector, users have become steadily more deeply integrated into the development process thanks to widespread adoption of user research methods. Game analysis is not an altogether new or independent field. It has root in and borrows largely from many existing field, such as usability inspection methods, business intelligence, statistics and data mining, among others. It is therefore necessary to provide a panoramic view on the key disciplines and concepts that are at the core of game analysis. Historically, game development
has not been data-driven, but this is changing as the benefits of adopting and adapting analysis to inform decision making across all levels of the industry are becoming generally known and accepted. The widespread adoption of data-driven business intelligence practices at operational, tactical and strategic levels in the game industry, combined with the integration of quantitative measures in user-oriental game research, has caused a paradigm shift. Quantitative data obtained via telemetry, market reports, QA system, benchmark tests, and numerous other sources all feed into business intelligence management, informing decision-making.
 
 
Generally, these basic metrics of game analysis can be placed in three broad categories: Acquisition, Monetization, and Engagement. The engagement is the most important, mainly for two reasons:
1. Some engagement metrics sit at the base of player lifetime value calculations, a metric that is used exclusively to ensure user acquisition with a positive return on investment.
2. Engagement relates closely to the games' funness. It is a measure of the degree to which your game fulfills, so to speak, its destiny.
 
In our research center, we are developing a system to collect players' physiological data and are developing an interactive tool enabling game analysis experts to observe the multi-channel collaborative data. Games module is a cross-platform to support many different games. Player biological information module includes the acquisition equipment such as electroencephalogram (EEG), Eye tracker, face reader and game joysticks etc. Character status module is to track player behavior inside of the virtual environment but not the players' actual physical status as player biological information module. Interactive Display of data is work for the cross platform display. Game data center module is the core of our project. It is responsible for game big data mainly including distributed Data Warehouse and real-time computing.
 
The aim is to provide multi-channel and interactive data enabling observation for correlations between data from eye tracking, EEG, facial expression, etc. It is facilitated by statistical data displays and by tagging key events in the data. An optimized user interface coupled with the large ultra-high resolution provided by a 4K monitor will aid in a unified and synchronized display and interactive access to the recorded data.
 

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