Abstract

There are plenty of domains as far as research in social media is concerned; Social Network, Video social media, image social media, research/ professional social media and so on. In the present work, we have focused on YouTube which is one of the pioneering amongst video social media. We have modeled the popularity dynamics of YouTube videos based on the information spread amongst the netizens and the number of subscribers for a particular video. An alternative approach to reach to our proposal has also been provided. In practice, the pace of the spread of information might vary because of various reasons such as quality of information, word of mouth, social causes etc. This transformation has been inculcated in the aforesaid modeling and results obtained on the view-count data sets of YouTube videos are very promising.

Highlights

  • IntroductionHumans have evolved from Paleolithic to Mesolithic/ Neolithic to Bronze to Iron age. From being a hunter & gatherer to a fully civilized society; humanity has progressed through different revolutions

  • ARPANET was initially funded by Advanced Research Projects Agency (ARPA) of the United States Department of Defense

  • We have proposed a methodical approach to understand popularity dynamics of YouTube videos based on the information spread amongst netizens including the role of subscribers for particular videos

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Summary

Introduction

Humans have evolved from Paleolithic to Mesolithic/ Neolithic to Bronze to Iron age. From being a hunter & gatherer to a fully civilized society; humanity has progressed through different revolutions. As popularity and number of viewers grew the video uploaders started getting the share of revenue from YouTube, which lead to the commercialization of videos. It evolved from “expressing the thoughts and emotions” to “source of revenue and expression of art”. YouTube introduced various feature to generate it user base for example “Subscribe” button is introduced so that if a user subscribed a channel than whenever video is uploaded on that channel, user receives a notification It has like dislike button along with comment section that allows user to express its views on the video. For YouTube and uploaders, it provides a blue print of how much revenue is generated and for advertisers it provides a time frame when to advertise on a particular video

Literature Review
Notations The notations used in this paper are explained as follows
An Alternate Formulation of the Aggrawal et al (2017a) Modeling Framework
Changed Point Based Modelling Framework
Model Validation The three proposed models as per the scenario described are
Description of Data Sets
Conclusions
Full Text
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