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During the course of the Complex Networks, we study the different concept regarding the complex computer networking. The main points upon which in these lecture slides focused are:Information Diffusion, Factors Influencing, Strength of Ties, Network Structure, Connected, Granovetter, Onnela, Kossinets, Interlocks, Adoption of Practices
Typology: Slides
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network structure: which nodes are connected? strength of ties: how strong are the connections?
Granovetter: the strength of weak ties J-P Onnela et al: strength of intermediate ties Kossinets et al: strength of backbone ties Davis: board interlocks and adoption of practices
Burt: Structural holes and good ideas Aral and van Alstyne: networks and information advantage
Lazer and Friedman: innovation
frequent contact affinity many mutual contacts
“forbidden triad”: strong ties are likely to “close”
Source: Granovetter, M. (1973). "The Strength of Weak Ties",
school kids and 1st^ through 8th^ choices of friends
will you reach more different kids by asking each kid to name their 2 best friends, or their 7 th^ & 8 th^ closest friend?
Source: M. van Alstyne, S. Aral. Networks, Information & Social Capital Docsity.com
M. S. Granovetter: The Strength of Weak Ties , AJS, 1973:
frequently (2+ times/week) 16.7% occasionally (more than once a year but < 2x week) 55.6% rarely 27.8%
contact directly works for/is the employer or is connected directly to employer
which paths yield the most up to date info? how many of the edges form the “backbone”?
source: Kossinets et al. “The structure of information pathways in a social communication network”Docsity.com
source: Onnela J. et.al. Structure and tie strengths in mobile communication networks
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infected individual infects neighbors with information at some rate
individuals must hear information (or observe behavior) from a number or fraction of friends before adopting
how do you pick individuals to “infect” such that your opinion prevails
http://projects.si.umich.edu/netlearn/NetLogo4/DiffusionCompetition.html
Infected
Healthy
Prob. β
Prob. δ
An SIR model consists of three group
Susceptible: Those who may contract the disease Infected: Those infected Recovered: Those with natural immunity or those that have died.
An SIS model consists of two group
Susceptible: Those who may contract the disease Infected: Those infected
aij ∈ {0,1}
aij = a ji
vi ( t )∈{ 0 , 1 }
farmers adopting new varieties of hybrid corn by observing what their neighbors were planting (Ryan and Gross, 1943) doctors prescribing new medication (Coleman et al. 1957) spread of obesity & happiness in social networks (Christakis and Fowler, 2008)
online behavioral data: Spread of Flickr photos & Digg stories (Lerman, 2007) joining LiveJournal groups & CS conferences (Backstrom et al. 2006) + others e.g. Anagnostopoulos et al. 2008
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time resolved data: if adoption time is shuffled, does it yield the same patterns? if edges are directed: does reversing the edge direction yield less predictive power?