Understanding videos at scale: How to extract insights for business research

Jasper Schwenzow, Jochen Hartmann, Amos Schikowsky and Mark Heitmann

Journal of Business Research, 2021, vol. 123, issue C, 367-379

Abstract: Video content has become a major component of total internet traffic. Growing bandwidth and computational power conspire with an increasing number of video editing tools, smartphones, and online platforms that have facilitated video production, distribution, and consumption by businesses and consumers alike. This makes video content relevant across business research disciplines. However, analyzing videos can be a cumbersome manual task. Automated techniques are scattered across technical publications and are often not directly accessible to business researchers. This article synthesizes the current state of the art and provides a consolidated tool to efficiently extract 109 video-based variables, requiring no programming knowledge. The variables include structural video characteristics such as colorfulness as well as advanced content-related features such as scene cuts or human face detection. The authors discuss the research potential of video mining, the types of video features of likely interest, and illustrate application using a practical example.

Keywords: Video mining; Image analysis; Object detection; Deep learning; Computer vision; Unstructured data (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:123:y:2021:i:c:p:367-379

DOI: 10.1016/j.jbusres.2020.09.059

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