The Experts below are selected from a list of 8178 Experts worldwide ranked by ideXlab platform

Carlos Fernandez - One of the best experts on this subject based on the ideXlab platform.

Luis De La Calle - One of the best experts on this subject based on the ideXlab platform.

  • The quantity and quality of Terrorism The DTV dataset
    Journal of Peace Research, 2011
    Co-Authors: Luis De La Calle, Ignacio Sánchez-cuenca
    Abstract:

    This article presents a dataset of fatalities of Domestic Terrorism in Western European countries for the period 1965–2005. The Domestic Terrorism Victims (DTV) dataset, unlike others such as TWEED...

  • Domestic Terrorism the hidden side of political violence
    Annual Review of Political Science, 2009
    Co-Authors: Ignacio Sanchezcuenca, Luis De La Calle
    Abstract:

    This article reviews the literature on the onset and dynamics of Domestic Terrorism, with special emphasis on the interactions between terrorist organizations, the state, and society. Because this literature has often been based on case studies, we seek to impose some structure to its findings. We challenge the distinction between Domestic and international Terrorism, which truncates the sample of violence, and we show that the actor-sense of Terrorism (violence carried out by underground organizations) is the most appropriate model for causal analysis. Terrorist organizations tend to emerge in developed countries in which the state is able to prevent the loss of control over any part of its territory. Terrorists take advantage of the state's mistakes (when, for example, it is over-repressive or makes ineffective concessions) in order to boost their support. Terrorists cannot survive without some degree of support. Consequently, levels of violence and targets are determined by social constraints.

Kyle T. Kattelman - One of the best experts on this subject based on the ideXlab platform.

  • Domestic Terrorism in the developing world: role of food security
    Journal of International Relations and Development, 2020
    Co-Authors: Nisha Bellinger, Kyle T. Kattelman
    Abstract:

    This article sheds light on the root causes of Terrorism by assessing the effect of food security on Domestic Terrorism among developing countries. Food security is a fundamental physiological need and captures a core well-being outcome. We argue that food insecurity creates grievances among citizens and increases demand among them for action against the government. Terrorist organisations provide the opportunity for citizens to channel their grievances against the government by resolving collective action problems and mobilising citizens. We demonstrate the link between food insecurity and Domestic Terrorism through quantitative analyses on a sample of 70 developing countries from 1980 to 2011. Our findings demonstrate the deleterious effects of food insecurity on peace in the developing world.

Wingyan Chung - One of the best experts on this subject based on the ideXlab platform.

  • categorizing temporal events a case study of Domestic Terrorism
    Intelligence and Security Informatics, 2012
    Co-Authors: Wingyan Chung
    Abstract:

    In many emergency incidents, multiple reports and information sources are often used to help intelligence and security personnel to understand the situation during a short time period. Proper categorization and analysis of this information could enhance the efficiency of handling this large amount of potentially conflicting information, thus contributing to saving lives. The study of categorization of temporal events in cyber security application is, however, not widely found. In this research, we developed an automated approach to categorizing temporal events described in textual documents. The approach consists of automatic indexing, term extraction, and automatic categorization. We conducted a case study of Domestic Terrorism where we analyzed 96 online news articles about a shooting tragedy that resulted in 6 deaths and 1 seriously injured. Analyses of different numbers of extracted textual features (from 20 to 100) used in the temporal categorization revealed a gradual improvement of classification accuracies across different algorithms used. Naive Bayes and SVM classification provided stable improvement (from 47% to 68%), whereas Neural Network had the highest accuracy when 70 features were used. The results provide new insights for researchers and intelligence personnel to understand the relationship between textual features and emergency event evolution.

  • building a web collection for online surveillance of u s Domestic Terrorism
    Intelligence and Security Informatics, 2012
    Co-Authors: Wingyan Chung, Wen Tang
    Abstract:

    As the trend of Domestic Terrorism grows rapidly, using web collections to support online surveillance should help intelligence and security personnel track down the sinister activities on the web. In this research, we have developed a collection of U.S. Domestic Terrorism websites and have conducted preliminary analysis of the sites' content and usage. We developed a novel approach to extracting textual, hyperlink, and usage information from websites. Our ongoing works include discovering hidden patterns from a collection of U.S. Domestic Terrorism websites and uncovering interesting usage and content patterns. This work should contribute to the area of online security surveillance using website data.

  • ISI - Building a web collection for online surveillance of U.S. Domestic Terrorism
    2012 IEEE International Conference on Intelligence and Security Informatics, 2012
    Co-Authors: Wingyan Chung, Wen Tang
    Abstract:

    As the trend of Domestic Terrorism grows rapidly, using web collections to support online surveillance should help intelligence and security personnel track down the sinister activities on the web. In this research, we have developed a collection of U.S. Domestic Terrorism websites and have conducted preliminary analysis of the sites' content and usage. We developed a novel approach to extracting textual, hyperlink, and usage information from websites. Our ongoing works include discovering hidden patterns from a collection of U.S. Domestic Terrorism websites and uncovering interesting usage and content patterns. This work should contribute to the area of online security surveillance using website data.

  • ISI - Categorizing temporal events: A case study of Domestic Terrorism
    2012 IEEE International Conference on Intelligence and Security Informatics, 2012
    Co-Authors: Wingyan Chung
    Abstract:

    In many emergency incidents, multiple reports and information sources are often used to help intelligence and security personnel to understand the situation during a short time period. Proper categorization and analysis of this information could enhance the efficiency of handling this large amount of potentially conflicting information, thus contributing to saving lives. The study of categorization of temporal events in cyber security application is, however, not widely found. In this research, we developed an automated approach to categorizing temporal events described in textual documents. The approach consists of automatic indexing, term extraction, and automatic categorization. We conducted a case study of Domestic Terrorism where we analyzed 96 online news articles about a shooting tragedy that resulted in 6 deaths and 1 seriously injured. Analyses of different numbers of extracted textual features (from 20 to 100) used in the temporal categorization revealed a gradual improvement of classification accuracies across different algorithms used. Naive Bayes and SVM classification provided stable improvement (from 47% to 68%), whereas Neural Network had the highest accuracy when 70 features were used. The results provide new insights for researchers and intelligence personnel to understand the relationship between textual features and emergency event evolution.

Debra Thomson - One of the best experts on this subject based on the ideXlab platform.