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

Abstract

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.