EPJ Data Science Highlight - Gaining historical and international relations insights from social media
- Published on Tuesday, 17 October 2017 11:43
As more and more people get their news from social media platforms, these become hosts to vast amounts of information on human behavior in relation to real-time events around the world. In a study published in EPJ Data Science, Vanessa Peña-Araya and team successfully match geopolitical interactions obtained from Twitter activity with real-world historical international relations.
(Guest post by Vanessa Peña-Araya, Mauricio Quezada, Denis Parra and Barbara Poblete, originally published on the SpringerOpen blog
Online social media platforms, like Twitter, Sina Weibo, or Facebook, have become very popular in recent years. They are primarily used to share personal experiences and to keep in touch with friends. Nevertheless, many users turn to these platforms as reliable sources to find real-time information about world events, such as the Ukrainian Crisis or recent natural disasters. In particular, Twitter has become one of the prefered sources on the Web for breaking news updates
- Published on Monday, 16 October 2017 18:15
In the summer of 2016 Pokémon Go took the world by storm. Millions of people across the globe descended on their streets, searching their neighbourhoods for monsters. Much has been reported on the health benefits that players gained from using the app; now, research published in EPJ Data Science explores how Pokémon Go was able to change the pulse of a city, encouraging people to use areas in ways they didn't previously.
(Guest post by Eduardo Graells-Garrido, originally published on SpringerOpen blog
The success of Pokémon Go is undeniable. People of all ages and everywhere in the world were using their mobile phones to go around their cities trying to catch the next pocket monster. But “PoGo” had an interesting, perhaps unintended, side-effect: not only did the game let you catch Pokémon in an augmented reality (AR) environment, it also motivated players to walk more and meet new people.
- Published on Thursday, 31 August 2017 14:25
In EPJ Data Science, Alice Patania and colleagues evaluate the collaborative interactions between scientists from a new perspective.
The structure of scientific collaborations has been the object of intense study both for its importance for innovation and scientific advancement, and as a model system for social group coordination and formation thanks to the availability of authorship data.
Over the last few years, complex networks approaches to this problem have yielded important insights and shaped our understanding of scientific communities. In our recently published article in EPJ Data Science, we propose to complement the picture provided by network tools with that coming from topological data analysis, which has at its core the notion of multi-agent interactions.