http://gephi.org/2008/semantic-graphs-french-ipr/ Semantic graphs of French IPR<http://gephi.org/2008/semantic-graphs-french-ipr/> 26 October 2008 [image: Main semantic graph of French intellectual property rights]<http://web-mining.fr/files/droit_auteur/carto_droit_auteur_generale.pdf> [image: Semantic graph of French contract rights]<http://web-mining.fr/files/droit_auteur/carto_droit_des_contrats.pdf> These work-in-progress maps are a study produced the last spring for the economist Yann Moulier-Boutang, law professor at the engineer school UTC<http://www.utc.fr/>. They represent the linked terms of vocabulary used on the Web to talk about the *intellectual property rights* in French language. Datasets come from Exalead SA <http://exalead.com/> (web/intranet search engine). Each node is a term and each edge exists when two terms or expressions are co-cited on a sufficient number of web pages, over more than 120,000 pages. *1283 expressions and 4984 co-citing links* have been selected, assuming a representative approach against an exhaustive one. *Semantic clusters* are represented with node colors in the general map. The contract rights map shows the *“imprint”* of this cluster (red nodes) inside the overall graph (in grey). The last image is a test to display the imprint of two meta-clusters : the vocabulary of intellectual property rights (in red) versus the one of industrial property rights (in blue). *How we did this ?* After an information extraction phase from the Exalead databases and a manual filtering, we made a GDF<http://guess.wikispot.org/The_GUESS_.gdf_format>file of row data (download it<http://gephi.org/wp-content/uploads/2008/10/ipr-semantic-graphe.gdf> and feel free to make your own viz !), spatialized the graph in Gephi with a *force-vector algorithm <http://iv.slis.indiana.edu/lm/lm-networks.html>* (in a nutshell, two nodes tied by an edge are graphically attracted to each other, otherwise they are rejected), applied some *filters* to colorize the nodes regarding to which semantic cluster they belong to, and then *export* the maps inSVG<http://en.wikipedia.org/wiki/SVG> format. The second part of the work consisted in softly improving the rendering and adding contextual informations like names of clusters, main terms clouds, legend…in Inkscape <http://www.inkscape.org/>, to finally build the PDF files. *Download the general map in PDF (50Mo)*<http://web-mining.fr/files/droit_auteur/carto_droit_auteur_generale.pdf> – Creative Commons by-nc-sa *Download the map of the contract rights in PDF (50Mo)*<http://web-mining.fr/files/droit_auteur/carto_droit_des_contrats.pdf> – Creative Commons by-nc-sa *Download the GDF file (graph not spatialized)<http://gephi.org/wp-content/uploads/2008/10/ipr-semantic-graphe.gdf> * (a shift in nodes positioning is normal) <http://gephi.org/wp-content/uploads/HLIC/799247b93c03cee9b8be3dcd78a8f7bf.png> Main semantic graph <http://gephi.org/wp-content/uploads/HLIC/49a5e4b1a1e3e095df8e631f93a22ef8.png> Zoom on the Free Software cluster <http://gephi.org/wp-content/uploads/HLIC/eda7e769d20e4f909355cd485229dd88.png> Contract rights map <http://gephi.org/wp-content/uploads/HLIC/d80ebcce8fbc601b374af71e2a39788e.png> Zoom on the core of contract rights Intellectual (red) vs industrial (blue) rights