Information Diffusion in Social Networks - School of Technology and ...

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Example: The SIR modelGiven a graph G and a special vertex v thathas a certain message (rumor).• Each node is in one of three states:Susceptible, Infected, Removed. Initial v isInfected and everyone else is Susceptible.• At each time step an edge (u,v) is chosen atrandom and if u is infected it sends themessage to v.• If v is S, it becomes I. If it is I it becomes R.• If v is R then u becomes R.
SIR: The Macro questionClearly, as long as there are infected nodes theprocess continues.Question: Will all the nodes have beeninfected for at least some time before theprocess ends?Ans: (Probably) depends on the topology. Fora complete graph the answer is no (Sudbury,J. Appl. Prob., 1985).
Page 1 and 2: Information Diffusion inSocial Netw
Page 3 and 4: Research aspects of OSNs• Sociolo
Page 5: Two aspects: Macro and MicroMicro:
Page 9 and 10: The way of EngineeringUse the obser
Page 11 and 12: Refining the questionThe Attributio
Page 13 and 14: The Model I• Users form a network
Page 15 and 16: The Model III• Each global tweet
Page 17 and 18: A reality check• The total weight
Page 19 and 20: Evolution in the viral regime800070
Page 21 and 22: Live longer, go further800070006000
Page 23 and 24: Topological study: Viral topicsMax
Page 25 and 26: Empirical cross-verification: Setup
Page 27 and 28: Large clusters in viral topics10 41
Page 29 and 30: The real data also has geography10
Page 31 and 32: The emerging science of big data•
Page 33 and 34: The research horizon..• …is unl

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