Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Social ties and their relevance to churn in mobile telecom networks
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Mobile call graphs: beyond power-law and lognormal distributions
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
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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.