Pulseweb project

This project is based on the automatic analysis of news related to food security issues in French language media (national and local).

Text-mining network analysis tools are used to identify the key themes discussed in the press at a given period. Each article is then associated with these automatically reconstructed topics wether they correpond to concerns expressed at the local level, or general statements and action at national/international level.

An online interface allows to visualize these maps, themes and news entries and to answer questions such as : Is an issue - concerning for example the impact of climatic change on food security - attracting more attention with time? How this specific issue relates with contiguous subjects (use of biofuel for example) ? Does the climatic change issue observed at a given time stem from, possibly various, past issue framings or is it a completely emergent topic ?

> For more information, please visit http://pulseweb.veilledynamique.com

Case studies with Un Global Pulse initiative: Monitoring Food Security Issues Through News Media



This project finds emerging trends and organizes thematic clusters in news related to food security issues in French language media from the last 8 years using automated text analysis, semantic clustering and networks theory.


The Complex Systems Institute of Paris Île-de-France (ISC-PIF, www.iscpif.fr) - CAMS, CNRS, CorText, CREA, Ecole Polytechnique, ESIEE, Formism, IFRIS, INRA-SenS - and The Institute For Research, Innovation and Society (IFRIS, www.ifris.org)


David Chavalarias, Jean-Phillipe Cointet, Lise Cornilleau, Tam Kien Duong, Andreļ Mogoutov, Camille Roth, Thierry Savy, Lionel Villard

Project Overview

This project explored whether is possible to track and comprehend thematic shifts in media attention through the automatic analysis of news articles.

To do so, we analyzed how the Francophone media reported on food security issues over the past 8 years. More than 20,000 related articles published between 2004 and 2011 were selected using an ontology of food security related terms. The contents of these articles were analyzed and organized into thematic clusters, which can be traced back to specific news articles or aggregated in a big picture representation. Semantic clustering methodologies and networks theory were used to automatically produce those clusters. The news items were also geo-located, enabling us to map how a given theme or issue is distributed over the world. Moreover, themes identified at successive time steps were reconnected into streams of content. A stream visualization illustrates how topics are articulated through time.

An interactive online interface visualizes these maps, themes and news entries to answer questions such as: Is an issue - concerning, for example, the impact of climatic change on food security - attracting more attention with time? How does a specific issue relate with contiguous subjects (use of biofuel, for example)?

The interactive platform can be explored online at:

This short video below, illustrates how it works:

Tubes with the same color form hyper-streams of a common topic. The analysis shows that as the 2008 global economic crisis unfolded, news coverage shifted from a focus on humanitarian issues (red) to food price volatility (blue), whereas in 2011, the news focus has shifted to social unrest (magenta).


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