Country-scale Exploratory Analysis of Call Detail Records through the Lens of Data Grid Models

TL;DR

This paper introduces a parameter-free, data-driven methodology for summarizing and exploring Call Detail Records (CDRs) data, enabling insights into human behavior and mobility through visualizations and multi-granularity analysis.

Contribution

It presents a novel, generic approach using data grid models for summarizing CDRs, applicable to various data types and demonstrated on real-world datasets from Ivory Coast.

Findings

Effective summarization of CDR data across multiple granularities

Applicable to network, temporal, and mobility data

Validated with real-world case studies from Ivory Coast

Abstract

Call Detail Records (CDRs) are data recorded by telecommunications companies, consisting of basic informations related to several dimensions of the calls made through the network: the source, destination, date and time of calls. CDRs data analysis has received much attention in the recent years since it might reveal valuable information about human behavior. It has shown high added value in many application domains like e.g., communities analysis or network planning. In this paper, we suggest a generic methodology for summarizing information contained in CDRs data. The method is based on a parameter-free estimation of the joint distribution of the variables that describe the calls. We also suggest several well-founded criteria that allows one to browse the summary at various granularities and to explore the summary by means of insightful visualizations. The method handles network graph data, temporal sequence data as well as user mobility data stemming from original CDRs data. We show the relevance of our methodology for various case studies on real-world CDRs data from Ivory Coast.