Slides used at 2010 SOCIALCOM conference: social and technical factors enabling propagation of breaking news in social network sites

1. Friendfeed breaking news:death of a public figure Matteo Magnani* - Danilo Montesi* - Luca Rossi° * University of Bologna, Dept. of Computer Science ° University of Urbino “Carlo Bo”, Dept. of Communication Studies http://larica.uniurb.it/sigsna

2. Introduction Social Network Sites: ability to spread information. How does breaking news propagate in a SNS? An empirical analysis of breaking news propagation on a real SNS to identify socio-technical patterns. Choice of a SNS. Monitoring. Extraction of posts related to some breaking news. Identification and interpretation of propagation patterns.

3. Friendfeed

4. SNS monitoring ≃ 10.500.000 posts ≃ 500.000 likes. ≃ 450.000 users. ≃ 15.000.000 edges (subscriptions). Downloadable from: http://larica.uniurb.it/sigsna/data/

5. In this talk: death of a public figure The news stroke Friendfeed users at 01.57 PM, Sep. 8. At that time only SkyTG24 was broadcasting the event. At the end of the day the death of Mike Bongiorno counted 585 comments, 276 during the first hour.

6. Data pre-processing 10,456,233 Language filter Keyword filter 196,350 Cleaning 939 Discussion reconstruction 936 1,473

7. Propagation in a social context Three patterns identified through a qualitative analysis of the posts. Explicit news propagation. Implicit news propagation through chatting. Mourning ritual of the networked public. Mike passed away! How has television changed? Mike passed away! Bye Mike! We’re missing you! Bye granpa Mike! Are we all a bunch of hypocrites mourning for a famous old man who died while thousand of people die everyday in the world? Why do we call Mike grandpa while we don’t care about our biological grandfathers? Bye Mike, you’ve been a milestone of our TV.

8. Role of mourning ritual

9. Following structured conversations Chat: depends on topic more than time. News: the winner takes all. Chat News (FE, 2nd top commented) 7 top commented threads about Mike’s death

10. Following distributed propagations

11. Propagation model

15. Research findings 1/2 Breaking news about the death of a public figure propagated through three main kinds of discussions: those giving the news, those expanding related topics, and R.I.P.. The first kind of discussion may evolve into the second. Their life cycles are significantly different. The first has a peak which decreases after short time. The second, made of longer messages, may stay alive longer, keeping the news active on the SNS. The third tends not to produce interactions. This is a direct consequence of the different social roles of these conversations.

16. Both kinds of message (first and second) may generate a high number of comments. For news messages time is relevant. Given the high rate of answers, an early message may have a saturation effect so that it aggregates the majority of discussions and limits the development of conversations on other similar messages. This does not seem to apply to chats, which may start days after the news occurred. The large majority of messages exchanged on the topic originates, directly or indirectly, from a single message (FE, in our case study). Messages inoculated by automated services may reach a large number of users directly following them, but: They do not generate comments. It appears that the majority of those users already learned the news. Research findings 2/2

17. Main message The propagation of breaking news follows patterns that can be understood only by considering the specific socio-technical features of the medium.

18. QUESTIONS?

19. Friendfeed breaking news:death of a public figure Matteo Magnani* - Danilo Montesi* - Luca Rossi° * University of Bologna, Dept. of Computer Science ° University of Urbino “Carlo Bo”, Dept. of Communication Studies Google: SIGSNA Twitter: sigsna matmagnani lrossi http://larica.uniurb.it/sigsna

20. Language Fidelity Index Language Fidelity Index: Number of Posts in a Language / Number of Posts of users with an entry in that language.

21. Death of Patrick Swayze: interaction network