netsi : networks research @ si
DESCRIPTION
NetSI : networks research @ SI. Lada Adamic, Jiang Yang, Eytan Bakshy, Xiao Wei, Matthew Simmons, Edwin Teng , David Huffaker. W hat we study. How networks shape information diffusion How information diffusion shapes networks Where you can find us: http://netsi.org. - PowerPoint PPT PresentationTRANSCRIPT
NetSI: networks research @ SI
NetSI: networks research @ SILada Adamic, Jiang Yang, Eytan Bakshy, Xiao Wei, Matthew Simmons, Edwin Teng, David Huffaker
What we studyHow networks shape information diffusionHow information diffusion shapes networksWhere you can find us:http://netsi.org
Social dynamics of information in virtual spaces (e.g. Second Life)Items diffusing through social network spread more rapidly but have limited rangeSellers who chat up customers enjoy more repeat business, but social interaction doesnt scale
Eytan, Matt, Edwin, Dave, & Lada, EC09, ICWSM10POSTER
Viral diffusion of social games on FacebookInvitation behaviorbatch vs. individual invitesinviting many vs. few friends is more predictive thandemographicssocial network structureBeing invitedmeans increased likelihood of staying longerGames that favor groupsgobble up dense cliques
Xiao, Jiang, and Lada collaborating with Ricardo Matsumura de Arajo and Manu RekhiPOSTERNetworks of trust:I rate you. You rate me. Should we do so publicly?
trust: private ratings, low correlationfriendship: public ratings, high correlationEdwin & Lada collaborating with Debra LauterbachPOSTER
Tracing memes across the web
duration in dayslength of phraseHow do memes change as they diffuselengthsentimentcontentHow does their diffusion/evolution depend on the underlying network structure?Matt & Lada collaborating with Eytan AdarPOSTERPredicting the Speed, Scale, and Range of Information Diffusion in TwitterTrace social diffusion through @username mentionsProperties of users (e.g. past popularity) more predictive than properties of tweets when it comes to speed, scale & range of diffusion
Jiang collaborating with Scott Counts, ICWSM 2010POSTERLongevity in Second LifeHow can you predict who will stay and who will leave?those who stay are chatting
direct chatsocial network tiemonetary transaction
Edwin & Lada, ICWSM10 posterPOSTERMapping interactions identifies Q&A forum types & experts9
Lada & Eytan collaborating with Jun Zhang & Mark Ackerman, WWW2007, WWW 2008How virtual points & real bucks influence participation in Q&A forums
Jiang, Xiao & Lada collaborating with Mark Ackerman, Tracy Liu, Yan Chen, ICWSM08, EC08, ICWSM09, ICWSM10Different kinds of networks:highly resistant bacteria hopping from hospital to hospitalfinancial trading networks
http://netsi.orgCome meet us at the sessionPOSTER
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12
34
Nth Family Member
Join
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Inte
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Yakuza LordsDiva Life
friendship rating A->B
frie
ndship
rating B
->A
1
2
3
4
5
6
7
1 2 3 4 5 6 7
Freq
102.5
103
103.5
104
104.5
105
105.5
106
trust A->B
trust ra
ting B
->A
1
3
4
5
6
1 3 4 5 6
Freq
103.5
104
104.5
105
105.5