Deployment of social nets in multi-layer model to identify Key individuals using majority voting

Social web and social media are evidenced to be a rich source of user-generated social content. Social media includes multiple numbers of social dimensions represented by different social networks. The identification of important player in these real-world social networks has been in high emphasis...

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Main Author:	Shah, Asadullah
Format:	Article
Language:	English
Published:	Springer Link 2019
Subjects:	T10.5 Communication of technical information
Online Access:	http://irep.iium.edu.my/74472/ http://irep.iium.edu.my/74472/ http://irep.iium.edu.my/74472/ http://irep.iium.edu.my/74472/1/74472_Deployment%20of%20Social%20Nets%20in%20Multi-layer%20model_complete.pdf

id	iium-74472
recordtype	eprints
spelling	iium-744722019-09-30T09:21:28Z http://irep.iium.edu.my/74472/ Deployment of social nets in multi-layer model to identify Key individuals using majority voting Shah, Asadullah T10.5 Communication of technical information Social web and social media are evidenced to be a rich source of user-generated social content. Social media includes multiple numbers of social dimensions represented by different social networks. The identification of important player in these real-world social networks has been in high emphasis due to its effectiveness in multiple disciplines, especially in Law enforcement areas working on dark networks. Many algorithms have been proposed to identify key players according to the objective of interest using suitable network centrality measures. This paper proposes a new perspective of dealing with key players identification by redefining it as a problem of “Key Individual Identification,” across multiple social dimensions. Research deals with each social dimension as a layer in the multiple-layer social network model. The proposed technique extracts a number of features from each network based on social network analysis. The features are assembled to formulate a global feature set representing the behaviors of individuals in all networks individually. The technique then attempts to find key individuals using hybrid classifiers. The results from all classifiers are formulated, and the final decision of an individual to be part of the Individual key set is based on majority voting. This novel technique gives good results on a number of known networks. Springer Link 2019-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/74472/1/74472_Deployment%20of%20Social%20Nets%20in%20Multi-layer%20model_complete.pdf Shah, Asadullah (2019) Deployment of social nets in multi-layer model to identify Key individuals using majority voting. Knowledge and Information Systems An international Journal, 58 (1). pp. 113-137. ISSN 0219-1377 E-ISSN 0219-3116 (In Press) https://link.springer.com/article/10.1007/s10115-018-1187-9 10.1007/s10115=018-1187-9
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	T10.5 Communication of technical information
spellingShingle	T10.5 Communication of technical information Shah, Asadullah Deployment of social nets in multi-layer model to identify Key individuals using majority voting
description	Social web and social media are evidenced to be a rich source of user-generated social content. Social media includes multiple numbers of social dimensions represented by different social networks. The identification of important player in these real-world social networks has been in high emphasis due to its effectiveness in multiple disciplines, especially in Law enforcement areas working on dark networks. Many algorithms have been proposed to identify key players according to the objective of interest using suitable network centrality measures. This paper proposes a new perspective of dealing with key players identification by redefining it as a problem of “Key Individual Identification,” across multiple social dimensions. Research deals with each social dimension as a layer in the multiple-layer social network model. The proposed technique extracts a number of features from each network based on social network analysis. The features are assembled to formulate a global feature set representing the behaviors of individuals in all networks individually. The technique then attempts to find key individuals using hybrid classifiers. The results from all classifiers are formulated, and the final decision of an individual to be part of the Individual key set is based on majority voting. This novel technique gives good results on a number of known networks.
format	Article
author	Shah, Asadullah
author_facet	Shah, Asadullah
author_sort	Shah, Asadullah
title	Deployment of social nets in multi-layer model to identify Key individuals using majority voting
title_short	Deployment of social nets in multi-layer model to identify Key individuals using majority voting
title_full	Deployment of social nets in multi-layer model to identify Key individuals using majority voting
title_fullStr	Deployment of social nets in multi-layer model to identify Key individuals using majority voting
title_full_unstemmed	Deployment of social nets in multi-layer model to identify Key individuals using majority voting
title_sort	deployment of social nets in multi-layer model to identify key individuals using majority voting
publisher	Springer Link
publishDate	2019
url	http://irep.iium.edu.my/74472/ http://irep.iium.edu.my/74472/ http://irep.iium.edu.my/74472/ http://irep.iium.edu.my/74472/1/74472_Deployment%20of%20Social%20Nets%20in%20Multi-layer%20model_complete.pdf
first_indexed	2023-09-18T21:45:27Z
last_indexed	2023-09-18T21:45:27Z
_version_	1777413418846781440

Deployment of social nets in multi-layer model to identify Key individuals using majority voting

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