Network analysis of Youtube videos based on keyword search with graph centrality approach

Author:

Surya Negara Edi,Andryani Ria,Amanda Riyan

Abstract

<p>Youtube is a social media that has billions of users, with this can be used as a promotional media, trends, business, and so forth. This study aims to analyze the correlation between Youtube videos by utilizing hashtags on video using graph theory. Data collection in this study uses scraping techniques taken from the Youtube website in the form of links, titles, keywords, and hashtags. The method used in this research is Social Network Analysis, the measurements used in this study are degree centrality and betweenness centrality. The results of this study indicate that the most popular hashtags with the keyword search for "viruses" are #KidflixPT, #Portugues, and #Mondo with degree centrality values equal to 0.071875. and the correlation between the most closely related videos about #Coronavirus with a value of betweenness centrality of 0.082626.</p>

Publisher

Institute of Advanced Engineering and Science

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Networks and Communications,Hardware and Architecture,Information Systems,Signal Processing

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Multiagent-based Youtube Content Discovery Bot;Proceedings of the International Conference on Advances in Social Networks Analysis and Mining;2023-11-06

2. Effectiveness of new algorithms for facial recognition based on deep neural networks;INT J NONLINEAR ANAL;2022

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