Mobile Phone Data: A Survey of Techniques, Features, and Applications

Area of Science:

• Computer Science
• Social Science
• Urban Planning

Background:

• Smartphones generate vast digital traces, offering insights into human behavior.
• Mobile phone data encompasses spatiotemporal and communication details vital for various research fields.
• Service providers collect extensive user activity data, including calls, texts, and internet usage.

Purpose of the Study:

• To survey and differentiate methods for assessing and predicting human communication and mobility patterns from mobile phone data.
• To identify key spatial, temporal, and call characteristics used in modeling human behavior.
• To provide a comprehensive overview of research published between 2013 and 2021.

Main Methods:

• Systematic literature review of 148 studies from eight major academic databases.
• Analysis of research focusing on mobile phone data for understanding communication and mobility.
• Categorization of methods based on their strengths and weaknesses.

Main Results:

• Mobile phone data provides rich insights into human mobility and communication networks.
• Extracted spatial, temporal, and call features are crucial for behavioral modeling.
• Diverse methodologies exist for analyzing this data, each with unique advantages.

Conclusions:

• Mobile phone data is a powerful tool for understanding complex human behaviors.
• Further research can refine methods for extracting and utilizing these digital traces.
• This survey aids researchers in selecting appropriate approaches for their studies.