EPJ Data Science is a platform for discussing the challenges of applying data-driven science to a range of research areas, with a focus on techno-socio-economic systems including human and animal social behavior and interaction, economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, and more.

Publisher
Springer
History
2012-present
Website
http://www.springerlink.com/content/2193-1127/

Some content from Wikipedia, licensed under CC BY-SA

How ideas go viral in academia

How ideas move through academia may depend on where those ideas come from—whether from big-name universities or less prestigious institutions—as much as their quality, a recent study from the University of Colorado Boulder ...

Are your tweets feeling well?

In the future, public health workers could monitor trends on social media to quickly identify a rise of influenza, depression or other health issues in a specific area, thanks to research at the Department of Energy's Pacific ...

Humanitarian efforts could be aided by AI

Researchers have developed an AI algorithm to accurately predict the gender of pre-paid mobile phone users, which could be useful in crises.

Predicting future sports rankings from evolving performance

Competitive sports and games are all about the performance of players and teams, which results in performance-based hierarchies. Because such performance is measurable and is the result of varied rules, sports and games are ...

Mining digital crumbs helps predict crowds' mobility

Getting urban planning right is no mean feat. It requires understanding how and when people travel between different places. This knowledge, in turn, helps in dimensioning roads and motorways and in scaling the capacity of ...

Expressing the value of data science in an ROI framework

Data science is rapidly becoming woven into the fabric of organizations of all sizes and types, and is driving significant societal and economic impact. Organizations are increasingly becoming data driven, investing in infrastructure, ...

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