2015 Impact factor 1.567

News / Highlights / Colloquium

EPJ Data Science Highlight - Tracking gene flow in marine plant evolution

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Genetic flow network for the Cymodocea nodosa marine plant. © A. P. Masucci et al.

Physicists and biologists apply Big Data statistical tools to study marine plant evolution

A new method that could give a deeper insight into evolutional biology by tracing directionality in gene migration has just appeared in EPJ Data Science. Paolo Masucci from the Centre for Advanced Spatial Analysis, at University College of London, UK, and colleagues identified the segregation of genes that a marine plant underwent during its evolution. They found that the exchange of genes, or gene flow, between populations of a marine plant went westward from the Mediterranean to the Atlantic. This methodology could also be used to estimate the information flow in complex networks, including other biological or social networks.

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EPJ Data Science Highlight - Driven by friendship

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© Emilio Ferrara

Dynamics of Facebook: the structure of the network drives friends to congregate into many small, highly interconnected communities

For the first time, the dynamics of how Facebook user communities are formed have been identified, revealing surprisingly few large communities and innumerable highly connected small-size communities. These findings are about to be published in EPJ Data Science by Italian scientist Emilio Ferrara, affiliated with both Indiana University in Bloomington, Indiana, USA and his home University of Messina. This work could ultimately help identify the most efficient way to spread information, such as advertising, or ideas over large networks.

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EPJ Data Science Highlight - Twitter data crunching: the new crystal ball

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Scientists have devised a means to predict the outcome of election-based processes such as TV talent shows through the big data analysis of tweets.

Fabio Ciulla from Northeastern University, Boston, USA, and his colleagues demonstrated that the elimination of contestants in TV talent shows based on public voting, such as American Idol, can be anticipated. They unveiled the predictive power of microblogging Twitter signals—used as a proxy for the general preference of an audience—in a study recently published in EPJ Data Science.

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EPJ Data Science - Countering crowd control collapse

EPJ Data Science - Countering crowd control collapse
© Angel Herrero de Frutos, iStockphotos, 138179229

Understanding crowd dynamics can prevent disaster at cultural or sports events.

Physicists investigating a recent crowd disaster in Germany found that one of the key causes was that at some point the crowd dynamics turned turbulent, akin to behaviour found in unstable fluid flows. The study, led by Dirk Helbing from the Risk Center at the Swiss Federal Institute of Technology ETH Zurich, Switzerland, is published in EPJ Data Science.

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EPJ Data Science - Positive words: the glue to social interaction

© Jennifer Stone/thinkstock.de

Words charged with a positive emotional content are used more frequently, thus enhancing human communication.

Scientists at ETH Zurich have studied the use of language, finding that words with a positive emotional content are more frequently used in written communication. This result supports the theory that social relations are enhanced by a positive bias in human communication. The study by David Garcia and his colleagues from the Chair of Systems Design is published in the first issue of the new SpringerOpen journal EPJ Data Science, and is freely available to the general public as an Open Access article.

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Editors-in-Chief
Frank Schweitzer and Alessandro Vespignani

Conference announcements

POSMOL 2017

Magnetic Island, Queensland, Australia, 22-24 July 2017