Game Data Science
Magy Seif El-Nasr, Alessandro Canossa, Truong-Huy D. Nguyen, and Anders Drachen
Abstract
This book is aimed at giving readers an introduction to the practical side of game data science and thus can be used a textbook for game analytics or game user research class or as a reference to self learners and enthusiasts. Game data science is a term that we use to denote a process composed of methods and techniques by which an analyst or a data scientist can make sense of data to allow decision makers in a game company to make informed decisions. This process involves: statistical analysis, visualization, abstraction of low-level data, machine learning and sequence data modeling. The book ... More
This book is aimed at giving readers an introduction to the practical side of game data science and thus can be used a textbook for game analytics or game user research class or as a reference to self learners and enthusiasts. Game data science is a term that we use to denote a process composed of methods and techniques by which an analyst or a data scientist can make sense of data to allow decision makers in a game company to make informed decisions. This process involves: statistical analysis, visualization, abstraction of low-level data, machine learning and sequence data modeling. The book introduces different methods borrowing from different fields including human computer interaction, machine learning, and data science, focusing on methods and techniques used by both industry and researchers within the field of games. The book examples and case studies specifically focus on gameplay log data. The book takes a practical stance on the subject by discussing theoretical foundation, practical approaches, and delves deeply into the different techniques proposed and used through labs, examples, and comprehensive surveys of various case studies from both industry and academia. Topics range from simple approaches to more advanced ones. No prior knowledge is required. The book is developed to be self contained and can be used as a good way to introduce the reader to data science and how it is applied to the filed of games.
Keywords:
Game data science,
game visualization,
game analytics,
player modeling
Bibliographic Information
| Print publication date: 2021 |
Print ISBN-13: 9780192897879 |
| Published to Oxford Scholarship Online: November 2021 |
DOI:10.1093/oso/9780192897879.001.0001 |
Authors
Affiliations are at time of print publication.
Magy Seif El-Nasr, author
Professor and Vice Chair of Serious Games, University of California at Santa Cruz
Alessandro Canossa, author
Professor, The Royal Danish Academy of Fine Arts Schools of Architecture, Design and Conservation
Truong-Huy D. Nguyen, author
Software Engineer, Google
Anders Drachen, author
Professor, Communications Director, Department of Computer Science, University of York. Co-Director, Digital Creativity Labs, Co-Director, Arena Research Cluster, Head of Analytics, Weavr
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