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A Study of social influence in diffusion of innovation over Facebook. Shaomei Wu email@example.com Information Science Cornell University Information Science Breakfast, Dec 5, 2008. Diffusion of Innovation.
Information Science Breakfast, Dec 5, 2008
“ Diffusion is the process in which an innovation is communicated through certain channels over time among the members of a social system. ”
–––– Everett M. Rogers *
* Rogers, Everett M. (2003). Diffusion of Innovations, 5th ed.. New York, NY: Free Press, pp 5-6
Statistically Equivalent *
*David Kempe, Jon Kleinberg, Eva Tardos. Maximizing the Spread of Influence through a Social Network.KDD, 2003
Question: how to estimate puv ?
Do individuals and the social relationship among them matter?
 Jure Leskovec, Mary McGlohon, Christos Faloutsos, Natalie Glance, Matthew Hurst,Cascading Behavior in Large Blog Graphs. SDM 2007.
 Jure Leskovec, Lada Adamic, Bernardo Huberman. The Dynamics of Viral Marketing. ACM Conference on Electronic Commerce (EC) 2006.
# of events attended/invited
# of photo tagged
# of wall posts
# of networks
# of groups participated
# of notes
Same political view?
Same culture background?
# of same networks
# of photos both tagged
# of groups both participated
# of events both attended
Same education level?
Same high school?
Same current city?
* all numerical features are normalized across examples.
Top weighted features:
8, sender_events_invited,4, sender_friend_count,11, sender_gender35, receiver_is_It's Complicated5, sender_wall_post_count,9, sender_note_count27. sender_is_In a Relationship
So, the story can be: when a sender who has been invited to greater number of events in Facebook, has more friends, wrote more Facebook notes (blog entries), is female, has less wall posts, in a relationship, tried to infect a person whose relationship status is “it’s complicated”, it’s more like the infection will happen compared to other cases.
current location(country/state/city), current school, current major, year of class, current workplace, current courses enrolled;
sex, sexual preference, dating interest, relationship interest, relationship status, birthday, political view, religious view, hometown address, previous school, previous workplace;
number of mutual networks they belong to, number of mutual friends;
activities, favorite books, favorite music, favorite movies, favorite TV shows, favorite quotas;
difference of numbers of friends, difference of wallpost counts, difference of counts of message sent and received, difference of counts of notes.