pkhiyara / Terrorist-Attack-Network-Visualization

An analysis of 9 terrorist attack networks across various countries between the years 2000 and 2005 using a Gephi network graph visualization with the goal of discovering patterns, similarities, connections, and potential relationships between one another’s actors.

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Terrorist Attack Network Visualization

An analysis of 9 terrorist attack networks across various countries between the years 2000 and 2005 using a Gephi network graph visualization with the goal of discovering patterns, similarities, connections, and potential relationships between one another’s actors. Apart from Gephi, Python was used with the Pandas and Numpy libraries to clean, manipulate, and merge all 18 datasets (nodes & relations) into 2 master datasets: all_nodes and all_relations. A Prezi data story that captures the project's results and conclusions can be accessed through the following link or viewed below:

Analyzing Terrorist Attack Networks Prezi Data Story

Analyzing Terrorist Attack Networks Data Story Slide 1 Analyzing Terrorist Attack Networks Data Story Slide 2 Analyzing Terrorist Attack Networks Data Story Slide 3 Analyzing Terrorist Attack Networks Data Story Slide 4 Analyzing Terrorist Attack Networks Data Story Slide 5 Analyzing Terrorist Attack Networks Data Story Slide 6 Analyzing Terrorist Attack Networks Data Story Slide 7 Analyzing Terrorist Attack Networks Data Story Slide 8 Analyzing Terrorist Attack Networks Data Story Slide 9

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An analysis of 9 terrorist attack networks across various countries between the years 2000 and 2005 using a Gephi network graph visualization with the goal of discovering patterns, similarities, connections, and potential relationships between one another’s actors.

License:MIT License


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Language:Jupyter Notebook 100.0%