Relation mining using cross correlation of multi domain social networks
Social network analysis has emerged as an important research area in intelligence analysis to facilitate decision maker in more informed decisions. With the passage of time social networks services are increasingly being used in legal and criminal investigations including understanding and tracking...
| Main Authors: | , , |
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| Format: | Proceeding Paper |
| Language: | English English English English |
| Published: |
2015
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| Online Access: | http://irep.iium.edu.my/48791/4/Relation_Mining_using_Cross_Correlation_of_Multi_Domain_Social_Networks-front_cover.pdf http://irep.iium.edu.my/48791/5/verso_page_asadullah.pdf http://irep.iium.edu.my/48791/6/toc_asadullah.pdf http://irep.iium.edu.my/48791/1/fozia-paper2015.pdf |
| _version_ | 1825649458818318336 |
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| author | Noor, Fozia Shah, Asadullah Ahmad Khan, Shoab |
| author_facet | Noor, Fozia Shah, Asadullah Ahmad Khan, Shoab |
| author_sort | Noor, Fozia |
| collection | IIUM |
| description | Social network analysis has emerged as an important research area in intelligence analysis to facilitate decision maker in more informed decisions. With the passage of time social networks services are increasingly being used in legal and criminal investigations including understanding and tracking of dark networks, i.e. illegal covert networks. Criminal organizations are well-suited to be studied using social network analysis as they consist of networks of individuals that span countries and continent using false identities over different networks to remain anonymous. There is great need to recognize the criminals carrying different fake identities to correctly track their immoral activities. This research article is focusing on devising a method which can be used to identify group of people i.e. criminals, terrorist or friends on different Social networks by analyzing patterns and performing correlations across different social network systems. Data integration using cross correlation is used to merge entities to form single focused networks. This single focused network also estimate the intensity of relationship between individuals in general networks based on the number of networks they are connected. To the best of our knowledge no such studies is done in the social network analysis, therefore this method is unique and offers innovations in making effective use of presence of people in different networks. |
| first_indexed | 2024-03-05T23:47:54Z |
| format | Proceeding Paper |
| id | oai:generic.eprints.org:48791 |
| institution | International Islamic University Malaysia |
| language | English English English English |
| last_indexed | 2024-03-05T23:47:54Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:487912021-01-18T05:57:17Z http://irep.iium.edu.my/48791/ Relation mining using cross correlation of multi domain social networks Noor, Fozia Shah, Asadullah Ahmad Khan, Shoab T10.5 Communication of technical information Social network analysis has emerged as an important research area in intelligence analysis to facilitate decision maker in more informed decisions. With the passage of time social networks services are increasingly being used in legal and criminal investigations including understanding and tracking of dark networks, i.e. illegal covert networks. Criminal organizations are well-suited to be studied using social network analysis as they consist of networks of individuals that span countries and continent using false identities over different networks to remain anonymous. There is great need to recognize the criminals carrying different fake identities to correctly track their immoral activities. This research article is focusing on devising a method which can be used to identify group of people i.e. criminals, terrorist or friends on different Social networks by analyzing patterns and performing correlations across different social network systems. Data integration using cross correlation is used to merge entities to form single focused networks. This single focused network also estimate the intensity of relationship between individuals in general networks based on the number of networks they are connected. To the best of our knowledge no such studies is done in the social network analysis, therefore this method is unique and offers innovations in making effective use of presence of people in different networks. 2015-11-02 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/48791/4/Relation_Mining_using_Cross_Correlation_of_Multi_Domain_Social_Networks-front_cover.pdf application/pdf en http://irep.iium.edu.my/48791/5/verso_page_asadullah.pdf application/pdf en http://irep.iium.edu.my/48791/6/toc_asadullah.pdf application/pdf en http://irep.iium.edu.my/48791/1/fozia-paper2015.pdf Noor, Fozia and Shah, Asadullah and Ahmad Khan, Shoab (2015) Relation mining using cross correlation of multi domain social networks. In: SAI Intelligent Systems Conference (IntelliSys), 2015, 10-11 November 2015, London, United Kingdom. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7361250&newsearch=true&queryText=Relation%20Mining%20using%20Cross%20Correlation%20of%20Multi%20Domain%20Social%20Networks |
| spellingShingle | T10.5 Communication of technical information Noor, Fozia Shah, Asadullah Ahmad Khan, Shoab Relation mining using cross correlation of multi domain social networks |
| title | Relation mining using cross correlation of multi domain social networks |
| title_full | Relation mining using cross correlation of multi domain social networks |
| title_fullStr | Relation mining using cross correlation of multi domain social networks |
| title_full_unstemmed | Relation mining using cross correlation of multi domain social networks |
| title_short | Relation mining using cross correlation of multi domain social networks |
| title_sort | relation mining using cross correlation of multi domain social networks |
| topic | T10.5 Communication of technical information |
| url | http://irep.iium.edu.my/48791/4/Relation_Mining_using_Cross_Correlation_of_Multi_Domain_Social_Networks-front_cover.pdf http://irep.iium.edu.my/48791/5/verso_page_asadullah.pdf http://irep.iium.edu.my/48791/6/toc_asadullah.pdf http://irep.iium.edu.my/48791/1/fozia-paper2015.pdf |
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