Video mining: Measuring visual information using automatic methods

Xi Li, Mengze Shi and Wang, Xin (Shane)

International Journal of Research in Marketing, 2019, vol. 36, issue 2, 216-231

Abstract: Marketers are becoming increasingly reliant on videos to market their products and services. However, there is no standard set of measures of visual information that can be applied to large datasets. This paper proposes two standard measures that can be automatically obtained from videos: visual variation and video content. The paper tests the measures on crowdfunding videos from a leading online crowdfunding website, and shows that the proposed measures have explanatory power on the funding outcomes of the projects. These measures can be effectively implemented and used for large datasets. Further, researchers can apply these measures to other sets of visual information, and marketers could use the research to guide their video design and improve their video marketing effectiveness.

Keywords: Video mining; Visual information; Visual variation; Video content (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (24)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167811619300217
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ijrema:v:36:y:2019:i:2:p:216-231

DOI: 10.1016/j.ijresmar.2019.02.004

Access Statistics for this article

International Journal of Research in Marketing is currently edited by Roland Rust

More articles in International Journal of Research in Marketing from Elsevier
Bibliographic data for series maintained by Catherine Liu ().