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SIGSNA:an empirical analysis of news propagationpath in social network sites. Luca Rossi –Universityof Urbino “Carlo Bo”luca.rossi@uniurb.it
Global phaenomenon, expressing cultural peculiarities.
Whatispropagation in Friendfeed?
Local Global User Prob. of exposition Avg. audience Time Delay of reception Avg. lifetime Howwe can observepropagation?
data All public entries(post and relatedcomments)(Sept. 6–Sept. 19 2009) ≃ 10.500.000 posts   ≃ 500.000 likes.   ≃ 450.000 users.  ≃ 15.000.000 di archi (subs).
case study: a propagation Mike Bongiorno (famousItalian TV host) died on Sept. 8 2010.The newsappears in Friendfeed at 01.57 PM:- First entry 130 comments - Allentries585 comments
Using timestamps and network of followers we have been able to track the  propagation paths identifying major hubs.
Short propagationchains Long propagationchains No propagation
Explicit news sharing is followed by chatting and discussion. This kind of activity contribute to news propagation “ Bye Mike! We’re missingyou!Bye granpa Mike! Mike, you’ve been a milestoneofour TV ” - Explicit news propagation. - Implicit news propagation. - Mourningritualof the networked public.
First entry has the highest informative function Most commented entry is a long and articulated discussion
Mass media system 2.0 ? Friendfeed Major Italian Newspapers(Il Corrieredella Sera, La Repubblica)
Mass media system 2.0 ? When the news hit the Friendfeed network only SkyTg24 wasbroadcastingit.  The selection code is up to the end user and hedecideswhenever a specific information is informative.
Mass media system 2.0 ? Is the evolutionof news/chat thatwehavedetectedsimilartocouple news/reportage?
More info, papers and data: http://larica.uniurb.it/sigsna SIGSNA is a joint research project with the department of Computer Science of the University of Bologna (Dr. MatteoMagnani) and it is partially founded by Telecom Italia.

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Gothenburg

  • 1. SIGSNA:an empirical analysis of news propagationpath in social network sites. Luca Rossi –Universityof Urbino “Carlo Bo”luca.rossi@uniurb.it
  • 2. Global phaenomenon, expressing cultural peculiarities.
  • 3.
  • 4.
  • 6. Local Global User Prob. of exposition Avg. audience Time Delay of reception Avg. lifetime Howwe can observepropagation?
  • 7. data All public entries(post and relatedcomments)(Sept. 6–Sept. 19 2009) ≃ 10.500.000 posts   ≃ 500.000 likes.   ≃ 450.000 users.  ≃ 15.000.000 di archi (subs).
  • 8. case study: a propagation Mike Bongiorno (famousItalian TV host) died on Sept. 8 2010.The newsappears in Friendfeed at 01.57 PM:- First entry 130 comments - Allentries585 comments
  • 9.
  • 10. Using timestamps and network of followers we have been able to track the propagation paths identifying major hubs.
  • 11. Short propagationchains Long propagationchains No propagation
  • 12.
  • 13.
  • 14.
  • 15. Explicit news sharing is followed by chatting and discussion. This kind of activity contribute to news propagation “ Bye Mike! We’re missingyou!Bye granpa Mike! Mike, you’ve been a milestoneofour TV ” - Explicit news propagation. - Implicit news propagation. - Mourningritualof the networked public.
  • 16. First entry has the highest informative function Most commented entry is a long and articulated discussion
  • 17. Mass media system 2.0 ? Friendfeed Major Italian Newspapers(Il Corrieredella Sera, La Repubblica)
  • 18. Mass media system 2.0 ? When the news hit the Friendfeed network only SkyTg24 wasbroadcastingit. The selection code is up to the end user and hedecideswhenever a specific information is informative.
  • 19. Mass media system 2.0 ? Is the evolutionof news/chat thatwehavedetectedsimilartocouple news/reportage?
  • 20. More info, papers and data: http://larica.uniurb.it/sigsna SIGSNA is a joint research project with the department of Computer Science of the University of Bologna (Dr. MatteoMagnani) and it is partially founded by Telecom Italia.