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 - The power of novel data to understand political sentiment

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In the aftermath of recent (and surprising) election results, it became evident that poll results do not tell the whole story about voters' intentions. In a study published in EPJ Data Science, researchers from the University of Leeds have mapped voter sentiment in all United Kingdom constituencies based on data from electronic petitions, achieving a good match with the results of the 2017 General Election.

(Guest post by Stephen Clark, Nik Lomax and Michelle A. Morris, originally published on SpringerOpen blog)

The EU referendum and 2017 General Election are two recent examples where polling companies failed to accurately predict the outcome of voter sentiment. Most predicted that the UK would vote to remain in the European Union and that the Conservative party would increase their parliamentary majority. When neither of these outcomes transpired there was much critique of the data sources and methods used to assess voter sentiment and opinion.

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EPJ Data Science Highlight - Instagram photos reveal predictive markers of depression

Right photograph has higher Hue (bluer), lower Saturation (grayer), and lower Brightness (darker) than left photograph. Instagram photos posted by depressed individuals had HSV values shifted towards those in the right photograph, compared with photos posted by healthy individuals.

Research published in EPJ Data Science finds that early-warning signs of depression can be detected in Instagram posts before a clinical diagnosis is made. Here to tell us how the image filter, colour and the number of faces in the post can all be predictors are authors of the study, Andrew G. Reece and Christopher M. Danforth.

Guest post by Andrew G. Reece and Christopher M. Danforth, originally published on SpringerOpen blog

When you’re feeling sad, the people around you probably know it. Moody playlists, slumped shoulders, drawn-out sighs – there are many ways we signal to the rest of the world when we’re having a down day. It’s not all that much of a stretch, then, to imagine your Instagram posts might look happier when you’re feeling happy, and sadder when you’re feeling sad.

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EPJ Plus Focus Point - Nuclear data for energy

During the past decades, new nuclear systems have been designed with the goals of ensuring the sustainability of nuclear energy, minimizing long-lived radioactive waste and improving the safety of nuclear reactors. This has led to the request for new or more precise nuclear data, either because reactions on isotopes neglected before have become important, or because new types of reactions have to be described. Nuclear data are in fact all the quantities necessary to describe the nuclear reactions occurring in a system.

In Europe, an important effort has been devoted to the collection of high quality nuclear data, and partially supported by the EURATOM framework programs: in particular ANDES (Accurate Nuclear Data for nuclear Energy Sustainability) and CHANDA (solving CHAllenges in Nuclear Data) in FP7. This EPJ Plus Focus Point issue presents part of the work performed during these programs.

All articles are freely accessible until 30 September 2017. For further information read the Editorial

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