Methods for quantifying effects of social unrest using credit card transaction data

Xiaowen Dong, Joachim Meyer, Erez Shmueli, Burçin Bozkaya, Alex Pentland

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Societal unrest and similar events are important for societies, but it is often difficult to quantify their effects on individuals, hindering a timely and effective policy-making in emergencies and in particular localized social shocks such as protests. Traditionally, effects are assessed through economic indicators or surveys with relatively low temporal and spatial resolutions. In this work, we compute two behavioral indexes, based on the use of credit card transaction data, for measuring the economic effects of a series of protests on consumer actions and personal consumption. Using data from a metropolitan area in an OECD country, we show that protests affect consumers’ shopping frequency and spending, but in noticeably different ways. The effects show strong temporal and spatial patterns, vary between neighborhoods and customers of different socio-demographical characteristics as well as between merchants of different categories, and suggest interesting subtleties in purchase behavior such as displaced or delayed shopping activities. Our method can generally serve for the real-time monitoring of the effects of major social shocks or events on urban economy and consumer sentiment, providing high-resolution and cost-effective measurement tools to complement traditional economic indicators.

Original languageEnglish
Article number8
JournalEPJ Data Science
Volume7
Issue number1
DOIs
StatePublished - 1 Dec 2018
Externally publishedYes

Keywords

  • Consumer behavior
  • Credit card transaction
  • Economic effect
  • Social shocks
  • Spatiotemporal pattern

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computer Science Applications
  • Computational Mathematics

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