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.
- Published on Monday, 04 December 2017 16:45
Nowadays, platforms like Twitter play a big role in the aftermath of disasters, such as natural disasters, mass shootings, or terror attacks, as people try to receive the latest information on what happened through social media channels. A new study published in EPJ Data Science shows how an analysis of social media responses to disasters might help us better understand the dynamic of the public’s attention during these events, what such an analysis shows about people’s attention spans and focus points in the aftermath of disasters, and how analyses like these could be performed in a cost-effective way.
(Guest post by Yu-Ru Lin, originally published on SpringerOpen blog)
EPJ Data Science Highlight - Sentiment analysis methods for understanding large-scale texts: a case for using continuum-scored words and word shift graphs
- Published on Wednesday, 29 November 2017 12:30
Due to the emergence and continuously increasing usage of social media services all over the world, it is now possible to estimate in real-time how entire groups of people are feeling at a given point. However, in order to be able interpret the available data correctly, the right tools and methods need to be used. A new article EPJ Data Science examines a range of such methods and shows their ability but also their limitations.
(Guest post by Andrew Reagan, originally published on SpringerOpen blog
As a grad student trying to understand the emotional content of some unreadably large collection of texts, a typical night in grad school can often go something like this: You’re up late at night planning a new research study, thinking about trying some of this fancy sentiment-based text analysis. You resort to your favorite search engine with the query “sentiment analysis package python.” We have all been there, except maybe with R instead of Python (the latter being my favorite).
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