Video mining : Measuring visual information using automatic methods
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 216-231 |
Number of pages | 16 |
Journal / Publication | International Journal of Research in Marketing |
Volume | 36 |
Issue number | 2 |
Online published | 25 Mar 2019 |
Publication status | Published - Jun 2019 |
Link(s)
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.
In: International Journal of Research in Marketing, Vol. 36, No. 2, 06.2019, p. 216-231.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review