A Bayesian Approach to Income Inference in a Communication Network
Computers and Society
2020-03-17 v1 Machine Learning
Social and Information Networks
Physics and Society
Abstract
The explosion of mobile phone communications in the last years occurs at a moment where data processing power increases exponentially. Thanks to those two changes in a global scale, the road has been opened to use mobile phone communications to generate inferences and characterizations of mobile phone users. In this work, we use the communication network, enriched by a set of users' attributes, to gain a better understanding of the demographic features of a population. Namely, we use call detail records and banking information to infer the income of each person in the graph.
Cite
@article{arxiv.1811.04246,
title = {A Bayesian Approach to Income Inference in a Communication Network},
author = {Martin Fixman and Ariel Berenstein and Jorge Brea and Martin Minnoni and Matias Travizano and Carlos Sarraute},
journal= {arXiv preprint arXiv:1811.04246},
year = {2020}
}
Comments
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2016). August 18, 2016