Data dump: A closer look at online social activity Lada Adamic School of Information, University of Michigan, Ann Arbor online social networking sites.

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Presentation transcript:

Data dump: A closer look at online social activity Lada Adamic School of Information, University of Michigan, Ann Arbor online social networking sites blogs phones instant messaging

Can we understand community dynamics? the political blogosphere, early 2005 detecting polarization analyzing discourse learning what brings communities together online Adamic & Glance, LinkKDD 2005

21 JawaReport 22 Vodka Pundit 23 Roger L Simon 24 Tim Blair 25 Andrew Sullivan 26 Instapundit 27 Blogs for Bush 28 LittleGreenFootballs 29 Belmont Club 30 Captain’s Quarters 31 Powerline 32 Hugh Hewitt 33 INDC journal 34 Real Clear Politics 35 Winds of Change 36 Allahpundit 37 Michelle Malkin 38 Wizbang 39 Dean’s World 40 Volokh 1 Digby’s Blog 2 James Walcott 3 Pandagon 4 blog.johnkerry.com 5 Oliver Willis 6 America Blog 7 Crooked Timber 8 Daily Kos 9 American Prospect 10 Eschaton 11 Wonkette 12 Talk Left 13 Political Wire 14 Talking Points Memo 15 Matthew Yglesias 16 Washington Monthly 17 MyDD 18 Juan Cole 19 Left Coaster 20 Bradford DeLong

Discussion of “forged documents” Liberals and conservatives differ in the topics they discuss

comment thread parody on Jim Henley’s ‘Unqualified Offerings’ Blog Communities and discourse

Different kinds of links - different interactions. Kuwait blog community 2006 Ali-Hasan and Adamic ICWSM 2007

roles: automatically inferring expertise in Question/Answer forums a fragment of Sun’s Java Forum Zhang

product recommendation network: medical study guideLeskovec, Adamic, Huberman, EC ‘06 Networks and viral marketing diffusion with costs

Power laws and information spread on networks Adamic, Lukose, Puniyani, Huberman, PRE 2001

Does high connectivity mean more influence when it comes to viral marketing? up to a point… influence is limited to a couple of dozen contacts

How influential is peer pressure? Will you cave in an buy if keep receiving recommendations?

Use of social ties for recommendations weakens the tie

recommendation success by book category lower success (1-3%)higher success (4-6%) not organizedorganized

niches VariableCoefficient # recommendations+ # senders- # recipients- small tightly knit communities more conducive to information spread

conclusions information diffuses on networks –path is influenced by structure –measured network is influenced by diffusion different interests/products bring people together incentives can modify social network structure –positively (new connections) –negatively (weakening existing connections)