Abstract
All the viewers of an online video do not watch a video at the same time. Consequently, on the basis of the behavioral measure of an individual who is moderately watching the videos earlier than others, viewers have been classified into viewer categories. Viewers’ categorization is much needed and has to be developed as viewers can lend a hand in targeting prospects for an online video and predict the continued sharing of the video. As per internet market literature, understanding and predicting view counts has not only resulted in generation of more traffic but has also acted as popularity metric for videos. Thereby, in the present work, based on analogy with a marketing science model we have studied the behavioral hypothesis for the modeling and quantification is offered in terms of varied and yet connected classes of viewers. With view count data on four YouTube videos, we have examined the diffusion of these videos over the time and illustrated the usefulness of the viewer categorization.
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Aggrawal, N., Arora, A. & Anand, A. Modeling and characterizing viewers of You Tube videos. Int J Syst Assur Eng Manag 9, 539–546 (2018). https://doi.org/10.1007/s13198-018-0700-6
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DOI: https://doi.org/10.1007/s13198-018-0700-6