DocumentCode :
3717276
Title :
Modeling social influences from call records and mobile web browsing histories
Author :
Jhao-Yin Li;Mi-Yen Yeh;Ming-Syan Chen;Jihg-Hong Lin
Author_Institution :
Department of Electrical Engineering, National Taiwan University
fYear :
2015
Firstpage :
1357
Lastpage :
1361
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.
Keywords :
"Companies","Mobile communication","History","Predictive models","Linear regression","Big data"
Publisher :
ieee
Conference_Titel :
Big Data (Big Data), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/BigData.2015.7363895
Filename :
7363895
Link To Document :
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