Beschreibung
The frequency of terrorist events in Pakistan has increased considerably in the past several years. These events are frequent and not random, making it important to identify useful patterns in their occurrences to assist counter-terrorism organizations. In this paper, we conduct such an analytical activity for the first time in Pakistan. We acquire data of terrorist events from reliable online sources, and apply data pre-processing techniques followed by cluster analysis. Based on statistical correlation, we discover clusters over the following combinations: 1) Event of Terrorism- Target of Terrorism, and 2) Event of Terrorism - Method of Terrorism. A more significant clustering is one which groups distinct combinations into separate clusters. We analyze these clusters along three dimensions: 1) annually for the time period 1988-2012, 2) for each Pakistani province, and 3) for different types of terrorist events. We also propose a statistic for gauging the intensity of terrorism, and analyze it along the same three dimensions. These can assist counter-terrorism authorities in thwarting future attacks and arresting the responsible criminals.
Autorenporträt
Dr. Tariq Mahmood is an Associate Professor at the prestigious Institute of Business Administration (IBA-Karachi). His research interests are big data analytics, deep learning and automated machine learning, particularly geared towards applications in the industry. He heads the BDA Lab at IBA-Karachi.
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