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New Formats, New Methods: Computational Approaches as a Way Forward for Media Entertainment Research

Author

Listed:
  • Johannes Breuer

    (Data Archive for the Social Sciences, GESIS—Leibniz Institute for the Social Sciences, Germany)

  • Tim Wulf

    (Department of Media and Communication, LMU Munich, Germany)

  • M. Rohangis Mohseni

    (Institute of Media and Communication Science, Ilmenau University of Technology, Germany)

Abstract

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.

Suggested Citation

  • Johannes Breuer & Tim Wulf & M. Rohangis Mohseni, 2020. "New Formats, New Methods: Computational Approaches as a Way Forward for Media Entertainment Research," Media and Communication, Cogitatio Press, vol. 8(3), pages 147-152.
    • Handle: RePEc:cog:meanco:v8:y:2020:i:3:p:147-152
    DOI: 10.17645/mac.v8i3.3530
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    References listed on IDEAS

    as
    1. Nathaniel Poor, 2020. "Open-Source’s Inspirations for Computational Social Science: Lessons from a Failed Analysis," Media and Communication, Cogitatio Press, vol. 8(3), pages 231-238.
    2. Steffen Lepa & Jochen Steffens & Martin Herzog & Hauke Egermann, 2020. "Popular Music as Entertainment Communication: How Perceived Semantic Expression Explains Liking of Previously Unknown Music," Media and Communication, Cogitatio Press, vol. 8(3), pages 191-204.
    3. Frank M. Schneider & Emese Domahidi & Felix Dietrich, 2020. "What Is Important When We Evaluate Movies? Insights from Computational Analysis of Online Reviews," Media and Communication, Cogitatio Press, vol. 8(3), pages 153-163.
    4. Frederic René Hopp & Jacob Taylor Fisher & René Weber, 2020. "A Graph-Learning Approach for Detecting Moral Conflict in Movie Scripts," Media and Communication, Cogitatio Press, vol. 8(3), pages 164-179.
    5. Frederic René Hopp & Jacob Taylor Fisher & René Weber, 2020. "A Graph-Learning Approach for Detecting Moral Conflict in Movie Scripts," Media and Communication, Cogitatio Press, vol. 8(3), pages 164-179.
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