Information spreading andviral 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 ...
Epidemiological models:“infected” users                   How a disease spreads?                                          ...
Governing equations• I – ignorant, s – spreaders, r – stiflers• Agent based simulations
FacebookWhy is good for information spreading •   Scale-free network •   Very easy to propagate viral messages •   Very la...
How to become viral?                         Importance of contagious ratePercentage “infected” users                     ...
How to become viral?                              Importance of degree kPercentage “infected” users
Detecting opinion leaders
What we achieved?• We are able to detect:  – Highest rank users (more contacts)  – Most influent (more feedback received) ...
Results     Are you getting the message?Time to         Random        Random +           Random+reach 1000                ...
Communities detection in Facebook
We found• High diversity of communities• Large superposition• Wide dispersion of clustering coefficient• Small resilience
ConclusionsWe made quantitative predictions:Conditions to achieve virality:  – high contagious rate  – target top N high r...
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Rumor spreading and viral marketing on facebook

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Rumor spreading and viral marketing on facebook

  1. 1. Information spreading andviral marketing on Facebook Armando Vieira http://armando.sairmais.com
  2. 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. 3. Epidemiological models:“infected” users How a disease spreads? time
  4. 4. Governing equations• I – ignorant, s – spreaders, r – stiflers• Agent based simulations
  5. 5. FacebookWhy 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. 6. How to become viral? Importance of contagious ratePercentage “infected” users Contagious rate / immunization rate
  7. 7. How to become viral? Importance of degree kPercentage “infected” users
  8. 8. Detecting opinion leaders
  9. 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. 10. Results Are you getting the message?Time to Random Random + Random+reach 1000 Top 10 Top 20visits (days)Test #1 45 10 4Test #2 16 7 1Test #3 - 17 12 #1 – video, #2 - contest, #3 – news
  11. 11. Communities detection in Facebook
  12. 12. We found• High diversity of communities• Large superposition• Wide dispersion of clustering coefficient• Small resilience
  13. 13. ConclusionsWe 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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