About EPJ

The European Physical Journal (EPJ) is a series of peer-reviewed journals covering the whole spectrum of physics and related interdisciplinary subjects. EPJ is committed to high scientific quality in publishing and is indexed in all main citation databases.

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EPJ Data Science Highlight - Controlling epidemics using mobile phone data

© CC0 Creative Commons, Pixabay

Mobile data can be (and has been) used to study a vast number of subjects related to human behavior. One of its potential applications is on epidemics, a complex field that is informed not only by healthcare, but also social interactions and human mobility. In this blog post, Stefania Rubrichi explains the context in which her team used a real mobile phone dataset in an attempt to better understand and tackle the spread of diseases. Their study was just published in the journal EPJ Data Science.

(Guest post by Stefania Rubrichi, originally published on the SpringerOpen blog)

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EPJ Data Science Highlight - Academic performance and behavioral patterns

Photo by Nathan Dumlao on Unsplash

In an article just published in EPJ Data Science, Valentin Kassarnig, Sune Lehmann and Andreas Bjerre-Nielsen look into smartphone data of undergraduate students to assess factors influencing social behavior and educational performance.

(Guest post by Valentin Kassarnig, Sune Lehmann & Andreas Bjerre-Nielsen, originally published on the SpringerOpen blog)

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EPJ Data Science Highlight - Discovering temporal regularities in retail customers’ shopping behaviour

(image via Pixabay, CC0 Creative Commons)

Why do we buy certain items when we buy them? A new study published in EPJ Data Science analyzes personal retail data to extract a temporal purchasing profile, which is able to summarize whether and when a customer makes a purchase. Its results show that certain patterns and types of shoppers are detectable, which can be used both by customers to enable personalized services, and by the retail market chain for providing offers and discounts tailored to the individual shoppers personal temporal profile.

(Guest post by Riccardo Guidotti and Anna Monreale, originally published on the SpringerOpen blog)

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