Exploring the Historical Behavior of Islamic State Groups: Latent Class Analysis and K-Modes Clustering Approach
Exploring the Historical Behavior of Islamic State Groups: Latent Class Analysis and K-Modes Clustering Approach
dc.contributor.advisor | Jaramillo Villegas, José Alfredo | |
dc.contributor.author | Varona Henao, Daniel | |
dc.contributor.author | Toquica Arango, Mateo | |
dc.date.accessioned | 2022-05-19T14:09:57Z | |
dc.date.available | 2022-05-19T14:09:57Z | |
dc.date.issued | 2021 | |
dc.description.abstract | Research on terrorism has always gravitated around qualitative methods and statistical techniques. Technology plays an essential role in terrorism and counterterrorism analysis by providing collections of large databases in many fields and the computational power to analyze them. Machine learning has shown new methods that could complement standard and well-established methodological approaches. This work contributes to the bridging of machine learning with terrorism studies by analyzing data with a classic statistical method Latent Class Analysis (LCA), and a machine learning method (K-modes). More formally, this work presents a mixed approach to analyze and cluster records from the Global Terrorism Database (GTD) referring to terrorist attacks belonging to the Islamic State. A diverse set of variables are considered, such as the type of weapons, targets, terrorist groups perpetrating the attacks, and geographic location. We identified three analysis periods by relying on a literature review and applied and contrasted LCA and K-Mode models for each period. This project aims to generate a record of how the periods were divided and identify the critical points for using the variables in the GTD database. Finally, we performed a data classification and generated an analysis for whoever requires it for these terrorist groups in the established periods. | eng |
dc.description.abstract | Este trabajo presenta un enfoque mixto para analizar y agrupar registros referentes a ataques terroristas pertenecientes al Estado Islámico, utilizando datos estructurados de la Global Terrorism Database (GTD) agrupados por ataques terroristas en función de diferentes variables a analizar, como el tipo de armas, objetivos que persigue el ataque, nombre del grupo terrorista, ubicación geográfica, entre otros; Para el posterior análisis de la información obtenida a través de artículos científicos que sustenten los hechos. A través de Kmodes se analizó la información obtenida, y se separó en grupos por características específicas y por bloques de años que permitieron analizar hechos históricos relevantes para la humanidad; Así, a través de los artículos mencionados anteriormente, se identificó la relación entre los datos ubicados en la base de datos GTD y los hechos. | spa |
dc.description.degreelevel | Maestría | |
dc.description.degreename | Magíster en Ingeniería de Sistemas y Computación | |
dc.description.tableofcontents | Contents 1 Introduction 7 1.1 Problem Description . . . . . . . . . . . . . . . . . . . . . . . . . 7 1.2 General and Specific Objectives . . . . . . . . . . . . . . . . . . . 8 1.2.1 General Objective . . . . . . . . . . . . . . . . . . . . . . . 8 1.2.2 Specific Objectives . . . . . . . . . . . . . . . . . . . . . . 8 1.3 Background and Justification . . . . . . . . . . . . . . . . . . . . 9 1.4 Viability and scope . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.5 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.5.1 Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . 10 1.5.2 Methodological Design . . . . . . . . . . . . . . . . . . . . 10 1.5.2.1 Data Mining . . . . . . . . . . . . . . . . . . . . 11 1.5.2.2 Identify Criteria . . . . . . . . . . . . . . . . . . 12 1.5.2.3 Period Division . . . . . . . . . . . . . . . . . . . 12 1.5.3 Optimal Clusters . . . . . . . . . . . . . . . . . . . . . . . 12 1.5.4 Implemented Models . . . . . . . . . . . . . . . . . . . . . 13 1.5.4.1 Latent Class Analysis . . . . . . . . . . . . . . . . 13 3 1.5.4.2 K-Modes . . . . . . . . . . . . . . . . . . . . . . 15 1.5.4.3 Model Comparison . . . . . . . . . . . . . . . . . 16 1.6 Project sustainability . . . . . . . . . . . . . . . . . . . . . . . . . 18 1.7 Administrative Aspects . . . . . . . . . . . . . . . . . . . . . . . . 18 1.7.1 Necessary Resources: Physical, Logistic, and Human. . . . 18 1.7.2 Sources of Funding . . . . . . . . . . . . . . . . . . . . . . 19 1.7.3 Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 2 State of the Art Review 21 2.1 Terrorism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2.2 Studies Where LCA and K-Modes are Applied . . . . . . . . . . . 27 2.2.1 LCA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 2.2.2 K-Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3 Theorethical Framework 32 3.1 Terrorism Study Techniques . . . . . . . . . . . . . . . . . . . . . 32 3.2 Terrorism Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 3.3 Islamic Terrorism . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 4 Thesis Development 41 4.1 Global Terrorism Database . . . . . . . . . . . . . . . . . . . . . . 41 4.2 Period Division . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.1 Period 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 4.2.2 Period 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.2.3 Period 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4.3 Data Processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 4 4.4 Exploratory data analysis . . . . . . . . . . . . . . . . . . . . . . 60 4.4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . 60 4.4.2 Lashkar-e-Islam . . . . . . . . . . . . . . . . . . . . . . . . 60 4.4.3 Al-Qaida in the Islamic Maghreb (AQIM) . . . . . . . . . . 62 4.4.4 Al-Qaida . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 4.4.5 Jemaah Islamiyah . . . . . . . . . . . . . . . . . . . . . . 67 4.5 Latent Class Analysis . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.5.1 Data Input . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 4.5.2 Command Options . . . . . . . . . . . . . . . . . . . . . . 70 4.6 K-Modes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 4.6.1 Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 4.6.2 Deploy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.7 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.7.1 Period 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 4.7.2 Period 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 5 Conclusions and Future Works 99 5.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.1.1 Data processing . . . . . . . . . . . . . . . . . . . . . . . . 99 5.1.2 Third period . . . . . . . . . . . . . . . . . . . . . . . . . 100 5.1.3 Groups evolution . . . . . . . . . . . . . . . . . . . . . . . 100 5.1.4 LCA and K-Modes . . . . . . . . . . . . . . . . . . . . . . . 101 5.1.5 Method comparison . . . . . . . . . . . . . . . . . . . . . 102 5.1.5.1 LCA List . . . . . . . . . . . . . . . . . . . . . . . 102 5.1.5.2 K-Modes list . . . . . . . . . . . . . . . . . . . . 103 | eng |
dc.format.extent | 113 Páginas | |
dc.format.mimetype | application/pdf | |
dc.identifier.instname | Universidad Tecnológica de Pereira | |
dc.identifier.reponame | Repositorio institucional Universidad Tecnológica de Pereira | |
dc.identifier.repourl | https://repositorio.utp.edu.co/home | |
dc.identifier.uri | https://hdl.handle.net/11059/14112 | |
dc.language.iso | eng | |
dc.publisher | Universidad Tecnológica de Pereira | |
dc.publisher.faculty | Facultad de Ingenierías | |
dc.publisher.place | Pereira | |
dc.publisher.program | Maestría en Ingeniería de Sistemas y Computación | |
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dc.rights | Manifiesto (Manifestamos) en este documento la voluntad de autorizar a la Biblioteca Jorge Roa Martínez de la Universidad Tecnológica de Pereira la publicación en el Repositorio institucional (http://biblioteca.utp.edu.co), la versión electrónica de la OBRA titulada: ________________________________________________________________________________________________ ________________________________________________________________________________________________ ________________________________________________________________________________________________ La Universidad Tecnológica de Pereira, entidad académica sin ánimo de lucro, queda por lo tanto facultada para ejercer plenamente la autorización anteriormente descrita en su actividad ordinaria de investigación, docencia y publicación. La autorización otorgada se ajusta a lo que establece la Ley 23 de 1982. Con todo, en mi (nuestra) condición de autor (es) me (nos) reservo (reservamos) los derechos morales de la OBRA antes citada con arreglo al artículo 30 de | spa |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | |
dc.rights.coar | http://purl.org/coar/access_right/c_abf2 | |
dc.rights.license | Atribución-NoComercial-SinDerivadas 4.0 Internacional (CC BY-NC-ND 4.0) | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.subject.ddc | 000 - Ciencias de la computación, información y obras generales::004 - Procesamiento de datos Ciencia de los computadores | |
dc.subject.other | Clustering methods | |
dc.subject.other | Digital simulation | |
dc.subject.other | Digital systems | |
dc.subject.proposal | Clustering | eng |
dc.subject.proposal | K- Models | eng |
dc.subject.proposal | Lantent class analysis | eng |
dc.title | Exploring the Historical Behavior of Islamic State Groups: Latent Class Analysis and K-Modes Clustering Approach | eng |
dc.type | Trabajo de grado - Maestría | |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | |
dc.type.content | Text | |
dc.type.driver | info:eu-repo/semantics/masterThesis | |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
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