Title: Multiple metric aware YouTube tutorial videos virality analysis

Authors: Niyati Aggrawal; Anuja Arora; Ponnurangam Kumaraguru

Addresses: CSE/IT Department, Jaypee Institute of Information Technology, Noida, India ' CSE/IT Department, Jaypee Institute of Information Technology, Noida, India ' Indraprastha Institute of Information Technology, A-404, Delhi, India

Abstract: This research paper focuses on the virality of content corresponding to user's reaction and proposes a multiple metric aware virality model (M2VM) which is beneficial to identify virality of content according to content characteristics and their resultant user reactions. The proposed M2VM assigns virality coefficient to each user reaction based on content properties/characteristics and predict a virality score of target content corresponding to measured user reactions' virality coefficients. To validate our proposed model we have chosen five tutorial-based theme videos of YouTube as case study. Thus in this research work, efforts have been made to analyse and understand users' selection intention towards tutorial videos on the basis of various video metrics. The prime objective of this research work is to analyse video characteristics role in identifying users' selection preference on the basis of video statistics and formulate various video metric corresponding to outcome to conclude the reaction of video characteristics over video virality. The research gives a practical exhibit of YouTube tutorial videos virality with respect to video characteristics mapping with video statistics.

Keywords: YouTube; virality model; video statistics; video metric; social network analysis; virality.

DOI: 10.1504/IJSNM.2017.091811

International Journal of Social Network Mining, 2017 Vol.2 No.4, pp.362 - 387

Received: 05 Sep 2016
Accepted: 22 Apr 2017
Published online: 18 May 2018 *

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