TY - GEN
T1 - Using the Panama Papers to explore the financial networks of the Middle East
AU - Rabab'Ah, Abdullateef
AU - Al-Ayyoub, Mahmoud
AU - Shehab, Mohammed A.
AU - Jararweh, Yaser
AU - Jansen, Bernard J.
N1 - Funding Information:
Jordan University of Science and Technology for supporting this work (Grant #20160081).
Publisher Copyright:
© 2016 Infonomics Society.
PY - 2017/2/14
Y1 - 2017/2/14
N2 - In what has been described as the WikiLeaks of the financial world, the release of millions of documents (known as the 'Panama Papers') have placed at the center of global media attention the elaborate ways used by some of the elite to hide their financial assets leading to serious allegation of financial corruption. In this work, we explore the information contained in these documents using social network analytics. Due to the large size of the network constructed from the Panama Papers, we limit our attention to a specific region, which is the Middle East. The analysis reveals that while the constructed network enjoys some typical characteristics, there are many interesting observations and properties worth discussing. Specifically, using the extracted network consisting of 37,442 nodes and 79,544 edges, our social network analysis finding show that, perhaps surprisingly, the nodes or the social network are not necessarily directly correlation with perceived financial influence.
AB - In what has been described as the WikiLeaks of the financial world, the release of millions of documents (known as the 'Panama Papers') have placed at the center of global media attention the elaborate ways used by some of the elite to hide their financial assets leading to serious allegation of financial corruption. In this work, we explore the information contained in these documents using social network analytics. Due to the large size of the network constructed from the Panama Papers, we limit our attention to a specific region, which is the Middle East. The analysis reveals that while the constructed network enjoys some typical characteristics, there are many interesting observations and properties worth discussing. Specifically, using the extracted network consisting of 37,442 nodes and 79,544 edges, our social network analysis finding show that, perhaps surprisingly, the nodes or the social network are not necessarily directly correlation with perceived financial influence.
UR - http://www.scopus.com/inward/record.url?scp=85016068101&partnerID=8YFLogxK
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U2 - 10.1109/ICITST.2016.7856674
DO - 10.1109/ICITST.2016.7856674
M3 - Conference contribution
AN - SCOPUS:85016068101
T3 - 2016 11th International Conference for Internet Technology and Secured Transactions, ICITST 2016
SP - 92
EP - 97
BT - 2016 11th International Conference for Internet Technology and Secured Transactions, ICITST 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference for Internet Technology and Secured Transactions, ICITST 2016
Y2 - 5 December 2016 through 7 December 2016
ER -