Key individual identification using dimensional relevance in the stratum of networks

Different aspects of social networks have increasingly been under investigation from last decades. The social network studies range in various viewpoints from the structural and node measures to the information diffusion processes. The key node identification has been one of the limelight topics of...

Full description

Bibliographic Details
Main Authors:	Shah, Asadullah, Noora, Fozia, Akram, Muhammad Usman, Shoab, Ahmad Khan
Format:	Article
Language:	English English
Published:	2019
Subjects:	T10.5 Communication of technical information
Online Access:	http://irep.iium.edu.my/74469/ http://irep.iium.edu.my/74469/ http://irep.iium.edu.my/74469/1/fozia-noor-paper2-2019.pdf http://irep.iium.edu.my/74469/7/74469_Key%20individual%20identification%20using%20dimensional%20relevance%20in%20the%20stratum%20of%20networks_Scopus.pdf

id	iium-74469
recordtype	eprints
spelling	iium-744692019-11-15T07:36:50Z http://irep.iium.edu.my/74469/ Key individual identification using dimensional relevance in the stratum of networks Shah, Asadullah Noora, Fozia Akram, Muhammad Usman Shoab, Ahmad Khan T10.5 Communication of technical information Different aspects of social networks have increasingly been under investigation from last decades. The social network studies range in various viewpoints from the structural and node measures to the information diffusion processes. The key node identification has been one of the limelight topics of social network analysis (SNA) specifically in a discipline like politics, criminology, marketing and etc. This research uses multiple networks constructed from the different social sites and real-life relationships to cover the multi-dimensional aspects of human relations. In the multi-relationship system, the different dimensions may differ in terms of relevance and weight. One of the most intriguing aspects of key node identification in the multi-dimensional system can be the consideration of dimensions relevance. This research covers the methodology to optimise the weights of dimensions using a number of centrality measures from each network layer covering multiple different objectives of interest. The study formulates the novel weighted feature set pertaining to layer relevance calculated based on layer relative importance through particle swarm optimization techniques. The framework applied ensemble-based approach on the weighted feature set along with node characteristics to predict key nodes in a network. The results are validated against ground truth data and accuracy achieved is promising. 2019 Article PeerReviewed application/pdf en http://irep.iium.edu.my/74469/1/fozia-noor-paper2-2019.pdf application/pdf en http://irep.iium.edu.my/74469/7/74469_Key%20individual%20identification%20using%20dimensional%20relevance%20in%20the%20stratum%20of%20networks_Scopus.pdf Shah, Asadullah and Noora, Fozia and Akram, Muhammad Usman and Shoab, Ahmad Khan (2019) Key individual identification using dimensional relevance in the stratum of networks. Journal of Intelligent & Fuzzy systems. pp. 1-15. (In Press) DOI:10.3233/JIFS-181517
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T10.5 Communication of technical information
spellingShingle	T10.5 Communication of technical information Shah, Asadullah Noora, Fozia Akram, Muhammad Usman Shoab, Ahmad Khan Key individual identification using dimensional relevance in the stratum of networks
description	Different aspects of social networks have increasingly been under investigation from last decades. The social network studies range in various viewpoints from the structural and node measures to the information diffusion processes. The key node identification has been one of the limelight topics of social network analysis (SNA) specifically in a discipline like politics, criminology, marketing and etc. This research uses multiple networks constructed from the different social sites and real-life relationships to cover the multi-dimensional aspects of human relations. In the multi-relationship system, the different dimensions may differ in terms of relevance and weight. One of the most intriguing aspects of key node identification in the multi-dimensional system can be the consideration of dimensions relevance. This research covers the methodology to optimise the weights of dimensions using a number of centrality measures from each network layer covering multiple different objectives of interest. The study formulates the novel weighted feature set pertaining to layer relevance calculated based on layer relative importance through particle swarm optimization techniques. The framework applied ensemble-based approach on the weighted feature set along with node characteristics to predict key nodes in a network. The results are validated against ground truth data and accuracy achieved is promising.
format	Article
author	Shah, Asadullah Noora, Fozia Akram, Muhammad Usman Shoab, Ahmad Khan
author_facet	Shah, Asadullah Noora, Fozia Akram, Muhammad Usman Shoab, Ahmad Khan
author_sort	Shah, Asadullah
title	Key individual identification using dimensional relevance in the stratum of networks
title_short	Key individual identification using dimensional relevance in the stratum of networks
title_full	Key individual identification using dimensional relevance in the stratum of networks
title_fullStr	Key individual identification using dimensional relevance in the stratum of networks
title_full_unstemmed	Key individual identification using dimensional relevance in the stratum of networks
title_sort	key individual identification using dimensional relevance in the stratum of networks
publishDate	2019
url	http://irep.iium.edu.my/74469/ http://irep.iium.edu.my/74469/ http://irep.iium.edu.my/74469/1/fozia-noor-paper2-2019.pdf http://irep.iium.edu.my/74469/7/74469_Key%20individual%20identification%20using%20dimensional%20relevance%20in%20the%20stratum%20of%20networks_Scopus.pdf
first_indexed	2023-09-18T21:45:26Z
last_indexed	2023-09-18T21:45:26Z
_version_	1777413418390650880

Key individual identification using dimensional relevance in the stratum of networks

Similar Items