At the beginning of our research we decided to identify a wide overview of the main topics around the controversy about Censorship and Terrorism. We visualized the Seealso connections in the Wikipedia page ‘Terrorism in the US’ to understand which thematic fields the network covers and its structure. We assigned a different color for each field. We analyze them closely and we found a bruch were religious terrorism was linked to censorship in US and media. Despite this brunch is composed by interesting nodes and reeflects our controversy, we thought that the visualization is still an outer overview, not well localized and needs a deeper analysis.


networkdefinition seealsology gephi+ sigma.js 1. network overview— network diameter— modularity2. layout— yfan hu— scaling 2— gravity 1— noverlap wikipedia page"consorship in the U.S."— distance 3 visualization HOW TO READ: website terminal software tool corpusdefinition visualization networkdefinition data-sourcedefinition queriesdefinition

This step started with the intention to investigate the web-network built around the controversy on information of terrorism and censorship. We created different networks on Wikipedia trying to understand in which thematic areas the controversy spread. The final network was build around the page “Censorship in the U.S.”, using Seealsology with distance 3. We decided to use Wikipedia firstly to explore unknown connections around and inside the controversy, but we found some limits for what concerns our topic. In particular, Wikipedia doesn't create a tight connection between terrorism (as wikipedia page) on one side, and censorship and media on the other; This is the reason why we chose the page about censorship and focused just on a branch inside of it, linked to terrorism.


Timestamp: 18/11/2016 - 24/11/2016

Data source: Wikipedia

The data contain a .gexf file created with Seealsology, containing the raw network of the visualization. Within the Gephi file you can explore nodes and edges spreadsheets, automatically organized in id, label, source and target.