Abstract
In this paper we propose models for inferring a social network of smartphone users. By applying the concept of information diffusion models to the log of application executions in smartphones, strength of relationships among users will be estimated as an optimization problem. Functions on time difference and application significance are employed to capture user behavior precisely. In addition, affiliation information of users is effectively utilized as an exogenous factor. Experimental results using 157 of smartphone users indicate that the proposed model outperforms naive methods and infers a social network appropriately. Especially, the model succeeds in capturing the important relations in user communities accurately.
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Ozaki, T., Etoh, M. (2011). Social Network Inference of Smartphone Users Based on Information Diffusion Models. In: Tang, J., King, I., Chen, L., Wang, J. (eds) Advanced Data Mining and Applications. ADMA 2011. Lecture Notes in Computer Science(), vol 7121. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25856-5_23
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DOI: https://doi.org/10.1007/978-3-642-25856-5_23
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