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  Predicting the Top-N Popularity of YouTube and Twitter Video's Using Early View Data  
  Authors : Christy Kunjumon; Dr.Radhakrishnan B
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In this paper, the proposed system jointly combines the properties of YouTube and Twitter. The linear regression method is used to predict the Top-N popular video's. This method is designed to improve the analysis of popular video's and their popularity trends. It is for understanding the video popularity characteristics and predicting the future video popularity. They have direct implications in various contexts such as service design, advertisement planning, network management and so on. The data are collected from YouTube and Twitter API's.


Published In : IJCSN Journal Volume 8, Issue 3

Date of Publication : June 2019

Pages : 254-257

Figures :03

Tables : 01


Christy Kunjumon : received her B.Tech (CSE) degree from University of Kerala in 2017. She is currently pursuing her Masters in Computer Science & Engineering from KTU.

Dr. Radhakrishnan B : is working as the Head of CSE department. He has more than 14 years experience in teaching and has published papers on data mining and image processing. His research interests include image processing, data mining, image mining.


popularity prediction, YouTube, social media, Multilayer Perceptron, linear regression.

In this paper, we have shown for a given YouTube videos for a specific period of time. The goal of the project is to use machine learning techniques to predict the popularity of YouTube videos and social feature network. Here the YouTube properties and twitter properties are considered as the input. Based on the properties, to predict the popularity of individual video. This study proposes a new prediction model based on multilayer perceptron and Linear Regression The result shows that the proposed model is better as compared with the previous models. Also, this model gives a consistent and accurate result.


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