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| Content Provider | ACM Digital Library |
|---|---|
| Author | Cebrian, Manuel Frias-Martinez, Enrique |
| Abstract | Word-of-mouth communication has been shown to play a key role in a variety of environments such as viral marketing and churn prediction. A family of algorithms, generally known as information spreading algorithms has been developed to model such pervasive behavior. Although these algorithms have produced good results, in general, they do not consider that the social network reconstructed to model the environment of an individual is limited by the information available. In this paper we study how the missing information (in the form of missing nodes and/or missing links) affects the spread of information in the well-known Dasgupta et al. (2008) algorithm. The results indicate that the error made grows logarithmically with the amount of information (links, nodes or both) unknown. |
| Starting Page | 1 |
| Ending Page | 4 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781605586946 |
| DOI | 10.1145/1641389.1641391 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2009-11-06 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Simulation Social network Word-of-mouth Link |
| Content Type | Text |
| Resource Type | Article |
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