Title: Extracting and Learning Social Networks out of Multilingual News
Authors: POULIQUEN BrunoTANEV HristoATKINSON Martin
Citation: Social Networks and application tools / International Workshop/ SoNet-08 (ISBN: 978-80-969700-9-4) p. 13-16
Publisher: SONET (SOcial NETworks)
Publication Year: 2008
JRC N°: JRC48864
URI: http://files.sonet.webnode.cz/200000028-d5263d6201/ExtractionSocialNetworks_Pouliquen-et-al-sonet08.pdf
http://publications.jrc.ec.europa.eu/repository/handle/JRC48864
Type: Contributions to Conferences
Abstract: Various kinds of social networks can be derived from the analysis of news articles. We present here our experience in building social networks by the extraction of relationships between entities all automatically derived from multilingual news articles. Unqualified relationships between persons can be extracted through simple co-occurrence statistics. Qualified relationships can be extracted using linguistic patterns. Our highly redundant sources (50,000 daily articles in 40 languages) are used to both validate our algorithms and strengthen pertinent relationships. Due to the amount of data we process these social networks provide a complex challenge for their useful visualization and navigation.
JRC Institute:Institute for the Protection and Security of the Citizen

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