A Hierarchical Approach for Investigating Social Features of a City from Mobile Phone Call Detail Records

TL;DR

This paper introduces a hierarchical analytical model that progressively explores social features of a city from mobile phone call detail records, enabling detailed insights into social activities and relationships.

Contribution

The paper presents a novel multi-layered approach that enhances social feature discovery from CDR data by iteratively building on previous analytical results.

Findings

Effective exploration of social activities and relationships

Hierarchical model improves detail and depth of social insights

Facilitates understanding of social groups in dense urban environments

Abstract

Cellphone service-providers continuously collect Call Detail Records (CDR) as a usage log containing spatio-temporal traces of phone users. We proposed a multi-layered hierarchical analytical model for large spatio-temporal datasets and applied that for the progressive exploration of social features of a city, e.g., social activities, relationships, and groups, from CDR. This approach utilizes CDR as the preliminary input for the initial layer, and analytical results from consecutive layers are added to the knowledge-base to be used in the subsequent layers to explore more detailed social features. Each subsequent layer uses the results from previous layers, facilitating the discovery of more in-depth social features not predictable in a single-layered approach using only raw CDR. This model starts with exploring aggregated overviews of the social features and gradually focuses on comprehensive details of social relationships and groups, which facilitates a novel approach for investigating CDR datasets for the progressive exploration of social features in a densely-populated city.