Modeling social influences from call records and mobile web browsing histories

Abstract

Nowadays, companies are usually strongly interested in discovering the latent social influences among their customers since the information is highly valuable to their marketing strategies. In this paper, we study how to model the influence probabilities among the customers of a telecommunication company by analyzing their call records and mobile web browsing histories. We first construct a directed network using the phone call records. We verify whether the statistical properties of our constructed network follow the commonly known social network properties. Next, we propose several heuristics to measure the influence probabilities between users in the constructed network by analyzing both the call records and the mobile web browsing histories. Finally, we evaluate our proposed measurements by two prediction tasks, including predicting the lengths of a call and estimating the number of common website visits between two users. The results show that our proposed measurements are effective with better prediction accuracy.

DOI: 10.1109/BigData.2015.7363895

4 Figures and Tables

Cite this paper

@article{Li2015ModelingSI, title={Modeling social influences from call records and mobile web browsing histories}, author={Jhao-Yin Li and Mi-Yen Yeh and Ming-Syan Chen and Jihg-Hong Lin}, journal={2015 IEEE International Conference on Big Data (Big Data)}, year={2015}, pages={1357-1361} }