{"id":3586,"date":"2019-07-12T20:43:48","date_gmt":"2019-07-12T20:43:48","guid":{"rendered":"https:\/\/notebooks.dataone.org\/?p=3586"},"modified":"2019-07-12T20:43:48","modified_gmt":"2019-07-12T20:43:48","slug":"week-8-visualization-with-gephi","status":"publish","type":"post","link":"https:\/\/notebooks.dataone.org\/citation-dataone\/week-8-visualization-with-gephi\/","title":{"rendered":"Week 8: Visualization with Gephi"},"content":{"rendered":"\n
Hoi! <\/p>\n\n\n\n
This week I’m happy to share with you some visualizations that reflect components of the DataONE publications and the articles that cite those publications. I created the visualizations with Gephi as I have not found a bibliometrics tool that allows you combine the cited and the citing articles in one visual. I am so thankful to have had Audrey (network analysis whiz and DataONE intern working on visualizing data in the Arctic Data Center repository<\/a>) help me along the way.<\/p>\n\n\n\n Network Stats<\/p>\n\n\n\n Modularity<\/strong><\/p>\n\n\n\n I ran modularity on the entire network in Gephi. This allows you to see various communities using the modularity algorithm presented by Vincent D Blondel, Jean-Loup Guillaume, Renaud Lambiotte, Etienne Lefebvre (2008<\/a>). In the visualization below, there are approximately 8 main communities and an overall modularity of 0.752. Once I ran the modularity statistic I looked at the articles’ titles in the network to see if they showed any topical cohesiveness and they did! Using this method I labeled 8 main preliminary topic communities: ecology + citizen science, data sharing, data management, data networks\/visualization, citizen science, problems and solutions, data gathering best practices, and big data\/data processing. Unfortunately, I couldn’t get the modularity to run in any informative way on just the citing articles so this analysis is based on both cited and citing articles. I’m going to explore more and see if I can get this to work.<\/p>\n\n\n\n