Mobile phone call data as a regional socio-economic proxy indicator

Area of Science:

• Computational Social Science
• Human Mobility Studies
• Socio-economic Indicator Development

Background:

• Anonymized call detail records (CDRs) enable novel studies of human dynamics.
• Mobility pattern models and socio-economic indicators can be developed beyond traditional data sources.

Purpose of the Study:

• To infer users' home and work locations from call frequencies in Côte d'Ivoire.
• To analyze regional mobility and calling patterns.
• To correlate these patterns with external data for socio-economic insights.

Main Methods:

• Inferring home and work sub-prefectures using call frequency and time-of-day data.
• Analyzing mobility and calling patterns across different regions.
• Correlating mobile phone data with news, census, economic activity, poverty index, and energy data.

Main Results:

• High correlations were observed between mobile phone data patterns and external socio-economic indicators.
• Mobile phone data provides diverse socio-economic insights.
• The study demonstrates the utility of CDRs for understanding human dynamics.

Conclusions:

• Mobile phone call data offers a valuable and affordable tool for socio-economic analysis in developing economies.
• These methods are particularly relevant for poverty reduction initiatives in resource-constrained settings.
• The findings highlight the potential of big data for policy-making.