Abstract
Different measures have been proposed to predict whether individuals will adopt a new behavior in online social networks, given the influence produced by their neighbors. In this paper, we show one can achieve significant improvement over these standard measures, extending them to consider a pair of time constraints. These constraints provide a better proxy for social influence, showing a stronger correlation to the probability of influence as well as the ability to predict influence.
Cite
CITATION STYLE
Marin, E., Guo, R., & Shakarian, P. (2017). Temporal analysis of influence to predict users’ adoption in online social networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10354 LNCS, pp. 254–261). Springer Verlag. https://doi.org/10.1007/978-3-319-60240-0_31
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