Detection of Jihadism in Social Networks Using Big Data Techniques Supported by Graphs and Fuzzy Clustering
المؤلفون المشاركون
Sánchez-Rebollo, Cristina
Puente, Cristina
Palacios, Rafael
Piriz, Claudia
Fuentes, Juan P.
Jarauta, Javier
المصدر
العدد
المجلد 2019، العدد 2019 (31 ديسمبر/كانون الأول 2019)، ص ص. 1-13، 13ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2019-03-10
دولة النشر
مصر
عدد الصفحات
13
التخصصات الرئيسية
الملخص EN
Social networks are being used by terrorist organizations to distribute messages with the intention of influencing people and recruiting new members.
The research presented in this paper focuses on the analysis of Twitter messages to detect the leaders orchestrating terrorist networks and their followers.
A big data architecture is proposed to analyze messages in real time in order to classify users according to different parameters like level of activity, the ability to influence other users, and the contents of their messages.
Graphs have been used to analyze how the messages propagate through the network, and this involves a study of the followers based on retweets and general impact on other users.
Then, fuzzy clustering techniques were used to classify users in profiles, with the advantage over other classifications techniques of providing a probability for each profile instead of a binary categorization.
Algorithms were tested using public database from Kaggle and other Twitter extraction techniques.
The resulting profiles detected automatically by the system were manually analyzed, and the parameters that describe each profile correspond to the type of information that any expert may expect.
Future applications are not limited to detecting terrorist activism.
Human resources departments can apply the power of profile identification to automatically classify candidates, security teams can detect undesirable clients in the financial or insurance sectors, and immigration officers can extract additional insights with these techniques.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Sánchez-Rebollo, Cristina& Puente, Cristina& Palacios, Rafael& Piriz, Claudia& Fuentes, Juan P.& Jarauta, Javier. 2019. Detection of Jihadism in Social Networks Using Big Data Techniques Supported by Graphs and Fuzzy Clustering. Complexity،Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1130978
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Sánchez-Rebollo, Cristina…[et al.]. Detection of Jihadism in Social Networks Using Big Data Techniques Supported by Graphs and Fuzzy Clustering. Complexity No. 2019 (2019), pp.1-13.
https://search.emarefa.net/detail/BIM-1130978
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Sánchez-Rebollo, Cristina& Puente, Cristina& Palacios, Rafael& Piriz, Claudia& Fuentes, Juan P.& Jarauta, Javier. Detection of Jihadism in Social Networks Using Big Data Techniques Supported by Graphs and Fuzzy Clustering. Complexity. 2019. Vol. 2019, no. 2019, pp.1-13.
https://search.emarefa.net/detail/BIM-1130978
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1130978
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