Video mining: Measuring visual information using automatic methods |
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| Authors: | Xi Li Mengze Shi Xin Wang |
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| Institution: | 1. City University of Hong Kong, Kowloon Tong, Hong Kong;2. Rotman School of Management, University of Toronto, Canada;3. Ivey Business School, Western University, London, Ontario N6G 0N1, Canada |
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| 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. |
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| Keywords: | Corresponding author Video mining Visual information Visual variation Video content |
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