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Rumor spreading and viral marketing on facebook

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Armando Vieira
Armando Vieira
1 of 13
Information spreading and viral marketing on Facebook Armando Vieira http://armando.sairmais.com
Problem • Determine how information spread over social networks – Facebook in particular • Locate relevant users to spread information • Message: viral or not? • Identify communities
Epidemiological models: “infected” users How a disease spreads? time
Governing equations • I – ignorant, s – spreaders, r – stiflers • Agent based simulations
Facebook Why is good for information spreading • Scale-free network • Very easy to propagate viral messages • Very large • Small world properties – easy to reach very distant nodes
How to become viral? Importance of contagious rate Percentage “infected” users Contagious rate / immunization rate
How to become viral? Importance of degree k Percentage “infected” users
Detecting opinion leaders
What we achieved? • We are able to detect: – Highest rank users (more contacts) – Most influent (more feedback received) – Most active (more messages / day) – Niche or generalist
Results Are you getting the message? Time to Random Random + Random+ reach 1000 Top 10 Top 20 visits (days) Test #1 45 10 4 Test #2 16 7 1 Test #3 - 17 12 #1 – video, #2 - contest, #3 – news
Communities detection in Facebook
We found • High diversity of communities • Large superposition • Wide dispersion of clustering coefficient • Small resilience
Conclusions We made quantitative predictions: Conditions to achieve virality: – high contagious rate – target top N high rank users, – identify communities and segment message armando.vieira@sairmais.com

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Rumor spreading and viral marketing on facebook

  • 1. Information spreading and viral marketing on Facebook Armando Vieira http://armando.sairmais.com
  • 2. Problem • Determine how information spread over social networks – Facebook in particular • Locate relevant users to spread information • Message: viral or not? • Identify communities
  • 3. Epidemiological models: “infected” users How a disease spreads? time
  • 4. Governing equations • I – ignorant, s – spreaders, r – stiflers • Agent based simulations
  • 5. Facebook Why is good for information spreading • Scale-free network • Very easy to propagate viral messages • Very large • Small world properties – easy to reach very distant nodes
  • 6. How to become viral? Importance of contagious rate Percentage “infected” users Contagious rate / immunization rate
  • 7. How to become viral? Importance of degree k Percentage “infected” users
  • 9. What we achieved? • We are able to detect: – Highest rank users (more contacts) – Most influent (more feedback received) – Most active (more messages / day) – Niche or generalist
  • 10. Results Are you getting the message? Time to Random Random + Random+ reach 1000 Top 10 Top 20 visits (days) Test #1 45 10 4 Test #2 16 7 1 Test #3 - 17 12 #1 – video, #2 - contest, #3 – news
  • 12. We found • High diversity of communities • Large superposition • Wide dispersion of clustering coefficient • Small resilience
  • 13. Conclusions We made quantitative predictions: Conditions to achieve virality: – high contagious rate – target top N high rank users, – identify communities and segment message armando.vieira@sairmais.com