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 - Listening to the changes in the urban rhythm

Photo: Pixabay, CC0 License

Cities evolve and undergo constant re-organisation as their population grow. This evolving process makes cities resilient and adaptive but also poses a challenge to analyse urban phenomena. For a long time, there has been evidence that suggests temporal and spatial regularities in crime, but so far studies about this have been based on the assumption that cities are static. A new study published in EPJ Data Science takes these factors into consideration and analyses spatio-temporal variation in criminal occurrences.

(Guest post by Marcos Oliveira & Ronaldo Menezes, originally published on the SpringerOpen blog)

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EPJ Data Science Highlight - A model to predict Airbnb distribution in cities

Photo by Erol Ahmed on Unsplash

The distribution of Airbnb listings has been the topic of much discussion among citizens and policy-makers, particularly in major cities. In an article published in EPJ Data Science, Giovanni Quattrone and colleagues looked into the many factors determining the spacial penetration of Airbnb in urban centers and developed a model that aims to predict this distribution in other cities. Among others, the presence of creative communities emerges as an important factor in the adoption of the housing plaftform.

(Guest post by Giovanni Quatronne, originally published on the SpringerOpen blog)

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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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