Extracting Skeleton of the Global Terrorism Network Based on m-Modified Topology Potential
المؤلفون المشاركون
Geng, Jing
Yuan, Hanning
Wang, Shuliang
Malang, Kanokwan
Phaphuangwittayakul, Aniwat
Lv, Yuanyuan
Lowdermilk, Matthew David
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-18، 18ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-16
دولة النشر
مصر
عدد الصفحات
18
التخصصات الرئيسية
الملخص EN
Skeleton network extraction is a crucial context in studying the core structure and essential information on complex networks.
The objective of this paper is to introduce the novel network extraction method, namely, TPKS-skeleton, for investigating the global terrorism network.
Our method aims to reduce the network’s size while preserving key topology and spatial features.
A TPKS-skeleton comprises three steps: node evaluation, similarity-based clustering, and skeleton network reconstruction.
The importance of skeleton nodes is quantified by the improved topology potential algorithm.
Similarity-based clustering is then integrated to allow detecting high incident concentrations and allocating the important nodes according to the event features and spatial distribution.
Finally, the skeleton network can be reconstructed by aggregating high-influential nodes from each cluster and their simplified edges.
To verify the efficiency of the proposed method, we carry out three classes of a network assessment framework: node-equivalence assessment, network-equivalence assessment, and spatial information assessment.
For each class, various assessment indexes were performed using the original network as a benchmark.
The results verify that our proposed TPKS-skeleton outperforms other competitive methods in particular node-equivalence by Spearman rank correlation and high network structural-equivalence defined by quadratic assignment procedure.
In the spatial perspective, the TPKS-skeleton network preserves reasonably all kinds of spatial information.
Our study paves the way to extract the optimal skeleton of the global terrorism network, which might be beneficial for counterterrorism and network analysis in wider areas.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Shuliang& Malang, Kanokwan& Yuan, Hanning& Phaphuangwittayakul, Aniwat& Lv, Yuanyuan& Lowdermilk, Matthew David…[et al.]. 2020. Extracting Skeleton of the Global Terrorism Network Based on m-Modified Topology Potential. Complexity،Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1143864
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Shuliang…[et al.]. Extracting Skeleton of the Global Terrorism Network Based on m-Modified Topology Potential. Complexity No. 2020 (2020), pp.1-18.
https://search.emarefa.net/detail/BIM-1143864
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Shuliang& Malang, Kanokwan& Yuan, Hanning& Phaphuangwittayakul, Aniwat& Lv, Yuanyuan& Lowdermilk, Matthew David…[et al.]. Extracting Skeleton of the Global Terrorism Network Based on m-Modified Topology Potential. Complexity. 2020. Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1143864
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1143864
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر