New Formats, New Methods
Computational Approaches as a Way Forward for Media Entertainment Research
Bibliographic Data
| ID | 21225044 |
|---|---|
| Authors | Johannes Breuer (0000-0001-5906-7873, GESIS - Leibniz Institute for the Social Sciences), Tim Wulf (0000-0002-2671-5106, LMU Klinikum), M Rohangis Mohseni (0000-0001-7686-8322, Technische Universität Ilmenau) |
| Year | 2020 |
| Volume | 8 |
| Issue | 3 |
| Pages | 147-152 |
| Publication date | 2020-08-13 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Media and Communication (JOURNAL) |
| Journal identifiers | ISSN: 2183-2439 • E-ISSN: 2183-2439 |
| Publisher | Cogitatio (PUBLISHER • PT) |
| DOI | 10.17645/mac.v8i3.3530 |
| OpenAlex | W3048742067 |
| Language | EN |
| Citations received | 2 |
| References cited | 16 |
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
Big data · Data science · Entertainment · Multimedia · Social media · World Wide Web · Computational and Text Analysis Methods · Computer Science · Media Influence and Health · Media Studies and Communication · Artificial Intelligence
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| Citations per year | 0.67 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |