Practical Social Network Analysis with Python by Krishna Raj P. M. & Ankith Mohan & K. G. Srinivasa

Author:Krishna Raj P. M. & Ankith Mohan & K. G. Srinivasa
Language: eng
Format: epub
ISBN: 9783319967462
Publisher: Springer International Publishing

In certain situations it is not just the timing of the contacts that matter but the pattern of timing also which can influence the severity of the epidemic. A timing pattern of particular interest is concurrency. A person is involved in concurrent partnerships if she has multiple active partnerships that overlap in time. These concurrent patterns cause the disease to circulate more vigorously through the network and enable any node with the disease to spread it to any other.

Reference [7] proposed a model which when given as input the social network graph with the edges labelled with probabilities of influence between users could predict the time by which a user may be expected to perform an action.

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