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Analyzing YouTube Subscription Networks: Insights and Challenges

This study explores the YouTube subscription network focusing on the channel "Machinima," which ranks fourth among the top 100 channels by subscriptions. Analyzed data shows 3,420 nodes with an average clustering coefficient of 0.085 and a betweenness score of 8245.130. The graph reveals one connected component, a diameter of 4, and a low graph density of 0.000466. Key challenges include identifying valid strategies for selecting videos or channels to assess the YouTube network effectively. This analysis aims to enhance understanding of social media interactions.

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Analyzing YouTube Subscription Networks: Insights and Challenges

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  1. Assumptions • Level to include is 2. • Videos has been transferred through other networks like Facebook. • Subscription network :directed graph • Public channel : since private channel (Obama,…) can not be parsed. • Number of nodes : 3420 • The used channel as seed node: http://www.youtube.com/user/machinima • It is the forth rank in the top 100 highest subscription (ref : http://vidstatsx.com/youtube-top-100-most-subscribed-channels)

  2. The Analyzed Channel

  3. Graph of Subscription “The obtained graph”

  4. Some Results • Average clustering coefficient: .085 • Average betweenness: 8245.130

  5. Cont. • Number of connected component : 1 • Diameter : 4 • Graph density : 0.000466 • Average in-degree =average out-degree = 1.593

  6. Cont.

  7. Some open problems • How we can select videos or channels to have valid judgment about YouTube network?

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