Name
Abstract | ||
|---|---|---|
Many algorithms for analyzing social networks assume that the structure of the network is known, but this is not always a reasonable assumption We wish to reconstruct an underlying network given data about how some property, such as disease, has spread through the network Properties may spread through a network in different ways: for instance, an individual may learn information as soon as one of his neighbors has learned that information, but political beliefs may follow a different type of model We create algorithms for discovering underlying networks that would give rise to the diffusion in these models. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-13562-0_38 | TAMC |
Keywords | Field | DocType |
different way,social network,underlying network,reasonable assumption,political belief,contagion information,network properties,different type,social networks,diffusion | Data science,Network science,Dynamic network analysis,Graph algorithms,Discrete mathematics,Complex contagion,Social network,Computer science,Evolving networks,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | ISBN |
6108 | 0302-9743 | 3-642-13561-7 |
Citations | PageRank | References |
3 | 0.39 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sucheta Soundarajan | 1 | 120 | 15.00 |
| John Hopcroft | 2 | 4245 | 1836.70 |