MultiScale modeling of Islamic organizations in UK

Nyunsu Kim, Sukru Tikves, Zheng Wang, Jonathan Githens-Mazer, Hasan Davulcu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper we utilize an efficient sparse inverse covariance matrix (precision matrix) estimation technique to identify a set of highly correlated discriminative perspectives. We develop a ranking system that utilizes ranked perspectives to map 26 UK Islamic organizations on a set of socio-cultural, political and behavioral scales based on their web corpus. We create a gold standard ranking of these organizations through an expertise elicitation tool. We compute expert-to-expert agreements, and we present experimental results comparing the performance of the QUIC based scaling system to another baseline method. The QUIC based algorithm not only outperforms the baseline method, but it is also the only system that consistently performs at area expert-level accuracies for all scales.

Original languageEnglish (US)
Title of host publicationProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013
PublisherIEEE Computer Society
Pages13-18
Number of pages6
ISBN (Print)9780769551371
DOIs
StatePublished - Jan 1 2013
Event2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013 - Washington, DC, United States
Duration: Sep 8 2013Sep 14 2013

Publication series

NameProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013

Other

Other2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013
Country/TerritoryUnited States
CityWashington, DC
Period9/8/139/14/13

ASJC Scopus subject areas

  • Software

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