Video mining : Measuring visual information using automatic methods

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

77 Scopus Citations
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Author(s)

  • Xi Li
  • Mengze Shi
  • Xin (Shane) Wang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)216-231
Number of pages16
Journal / PublicationInternational Journal of Research in Marketing
Volume36
Issue number2
Online published25 Mar 2019
Publication statusPublished - Jun 2019

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.

Research Area(s)

  • Video content, Video mining, Visual information, Visual variation

Bibliographic Note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Citation Format(s)

Video mining: Measuring visual information using automatic methods. / Li, Xi; Shi, Mengze; Wang, Xin (Shane).
In: International Journal of Research in Marketing, Vol. 36, No. 2, 06.2019, p. 216-231.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review