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Defence of dissertation in the field of computer science, Max Sjöblom, M.Sc. (Tech.)

Why do people watch others play games?
Photo by Caspar Camille Rubin on Unsplash

Max Sjöblom, M.Sc. (Tech.), will defend the dissertation "Spectating play: investigating motivations for watching others play games" on Thursday 18 April 2019 at 12 noon in Aalto University School of Science, lecture hall TU2, Maarintie 8, Espoo. The dissertation looks at the motivations for watching others play video games.

Watching others play games is not exactly a new thing. In fact, many of us might have childhood memories of sitting on a couch next to a friend or sibling, and watching them play rather than grabbing the controller ourselves. However, the past ten years have seen a huge boom in watching others play games, through services such as YouTube and Twitch, and the cultural phenomenon of competitive gaming, or esports. In fact, esports is one of the fastest growing entertainment industries in the world at the moment, attracting hundreds of millions of fans the world over.

The goal of this dissertation is to investigate the motivations for watching others play games and help understand this new form of media consumption. The data used in the publications that form this dissertation was obtained through international online surveys, gathering thousands of respondents.

This dissertation both helps understand the motivations for watching the live-streaming of games (Twitch), as well as why esports spectators choose to engage in their activity. Additionally, the dissertation examines various content types within streaming in greater detail.

The results of this dissertation help companies operating in the games and media industries to better understand their users, and to develop better products and services for these consumers. The research conducted in this dissertation ties closely to the broader games and media research field.

Opponent: Professor Mia Consalvo, Concordia University, Canada

Custos: Professor Perttu Hämäläinen, Aalto University School of Science, Department of Computer Science

Electronic dissertation: http://urn.fi/URN:ISBN:978-952-60-8470-1

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