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 - 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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EPJ Data Science Highlight – The science behind what makes a bestselling book

Photo by Anastasia Zhenina on Unsplash

Books that are fiction, thrillers or mysteries, have high initial sales numbers and are released around Christmas are more likely to be bestsellers, according to a study published in EPJ Data Science

(This post was originally published on the SpringerOpen blog)

A team of researchers from Northeastern University, Boston, used a big data approach to investigate what makes a book successful. By evaluating data from the New York Times Bestseller Lists from 2008 to 2016, they developed a formula to predict if a book would be a bestseller.

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EPJ Data Science Highlight - Urban form and socio-economics: what is the link?

Although urbanization has many advantages, one of its biggest drawbacks is the rise in socio-economic inequality. There have been some attempts at a qualitative analysis of the relationship between certain city features and social inequality, but these kinds of analyses are hard to replicate. A new research article published in EPJ Data Science proposes a new quantitative computer-based method for how to better understand the link between cites and social inequalities.

(Guest post by Alessandro Venerandi, originally published on the SpringerOpen blog)

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