2018 Impact factor 1.660
Special Topics

EPJ Data Science Highlight - What ‘Twitch Plays Pokémon’ tells us about crowd behavior

No one would deny that the behavior of the people we know, and even of our own, can radically change depending on those who surround us. The problem of understanding how being in a group changes the way we behave has been subject of intense research in psychology since the beginning of the past century. The beginning of the XXI century gave rise to a new kind of group: the online crowds. Nowadays, it is no longer necessary to have all individuals in the same place in order to have a ‘crowd’. What is more, it is possible to connect together thousands, even millions, of individuals in a matter of minutes.

In the work recently published in EPJ Data Science, we study one such occasion that gathered millions of users: Twitch Plays Pokémon.

Continue reading the guest post by Alberto Aleta on the SpringerOpen blog.

EPJ Data Science Highlight - What can we learn from billions of food purchases derived from fidelity cards?

© Map & Visualization: Tobias Kauer

For your health, what you eat is more important than what you earn.

This result comes from our latest project “Poor but Healthy”, which was published in EPJ Data Science, and comes with a @tobi_vierzwo’s stunningly “beautiful map of London” that author Daniele Quercia invites everyone to explore.

By combining 1.6B food item purchases with 1.1B medical prescriptions for the entire city of London for one year, researchers discovered that, to predict health outcomes, socio-economic conditions matter less than what previous research has shown: despite being of lower-income, certain areas are healthy, and that is because of what their residents eat.

Read the full blog post on Medium.

EPJ Data Science Highlight - How news outlets target audiences

© Photo by Kaboompics .com from Pexels

The mass media is one of the social forces with the most active transformative power. However, news reach people unequally. Many factors shape the distribution and influence of news media coverage. Some of these factors are the geographic reach of newspapers (national versus regional newspapers), the direct targeting of specific sectors of the population, and/or the political ideology of the media outlet itself.

In a recent article in EPJ Data Science, Erick Elejalde, from the L3S Research Centre in Hannover, Germany, explains how their work helps to identify whether or not an outlet’s coverage deviates from the purely geographic influence to a more sophisticated behavior involving the weight of political and socioeconomic interests.

Read the post on the SpringerOpen blog.

Managing Editors
Anne Ruimy (EDP Sciences) and Sabine Lehr (Springer-Verlag)
Dear Sabine and Isabelle,
Thank you so much for all your help and excellent work you did on the EPJ ST volume "Nonlinear Dynamics of Deterministic and Stochastic Systems: Unraveling Complexity". This was a great experience and collaboration.

Alexander Neiman (on behalf of the guest editors), Ohio University, Athens, USA
Editor EPJ Special Topics 222/10, 2013

ISSN: 1951-6355 (Print Edition)
ISSN: 1951-6401 (Electronic Edition)

© EDP Sciences and Springer-Verlag