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New Formats, New Methods: Computational Approaches as a Way Forward for Media Entertainment Research
Author(s) -
Johannes Breuer,
Tim Wulf,
M. Rohangis Mohseni
Publication year - 2020
Publication title -
media and communication
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 19
ISSN - 2183-2439
DOI - 10.17645/mac.v8i3.3530
Subject(s) - entertainment , computer science , social media , data science , field (mathematics) , multimedia , set (abstract data type) , perspective (graphical) , big data , world wide web , artificial intelligence , mathematics , pure mathematics , programming language , art , visual arts , operating system
The rise of new technologies and platforms, such as mobile devices and streaming services, has substantially changed the media entertainment landscape and continues to do so. Since its subject of study is changing constantly and rapidly, research on media entertainment has to be quick to adapt. This need to quickly react and adapt not only relates to the questions researchers need to ask but also to the methods they need to employ to answer those questions. Over the last few years, the field of computational social science has been developing and using methods for the collection and analysis of data that can be used to study the use, content, and effects of entertainment media. These methods provide ample opportunities for this area of research and can help in overcoming some of the limitations of self-report data and manual content analyses that most of the research on media entertainment is based on. However, they also have their own set of challenges that researchers need to be aware of and address to make (full) use of them. This thematic issue brings together studies employing computational methods to investigate different types and facets of media entertainment. These studies cover a wide range of entertainment media, data types, and analysis methods, and clearly highlight the potential of computational approaches to media entertainment research. At the same time, the articles also include a critical perspective, openly discuss the challenges and limitations of computational methods, and provide useful suggestions for moving this nascent field forward.

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