What Banking and Phone Data Tell us about the Socioeconomic Groups and Their Consumption Patterns?
| Autor: | Martin Minnoni, Luis C. Reyes, Ángel F. Agudo-Peregrina, Diego Pérez, Martin Langberg |
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| Rok vydání: | 2018 |
| Předmět: |
Consumption (economics)
education.field_of_study Computer science business.industry Population Big data 1. No poverty 02 engineering and technology Work (electrical) Phone 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Social media Marketing education business Social network analysis Socioeconomic status |
| Zdroj: | 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) ASONAM |
| DOI: | 10.1109/asonam.2018.8508330 |
| Popis: | This paper makes use of a large dataset of anonymized banking transactions and phone calls to classify individuals into socioeconomic groups (SEGs) and social networks, determine their consumption patterns, and compare the latter with equivalent information available from household surveys. The results obtained demonstrate that classification into SEGs by aggregated bank income provides a robust breakdown of the population that is validated by a social network analysis of the phone data. In addition, the spending profile obtained for each SEG shows that individuals behave similarly according to their income and their spending can be accurately categorized. Furthermore, the consumption patterns obtained from this novel approach can be contrasted directly with those obtained from national household surveys, potentially overcoming some of the limitations of traditional approaches in terms of coverage and inclusiveness. The work presented here shows the feasibility and capabilities of Big Data sources and tools to understand the consumption behavior of the population. |
| Databáze: | OpenAIRE |
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