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Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing

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Published in:Foundations of Computing and Decision Sciences
Format: Online Article RSS Article
Published: 2025
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container_title Foundations of Computing and Decision Sciences
description
discipline_display Computer Science
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format Online Article
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genre Journal Article
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institution FRELIP
journal_source_facet Foundations of Computing and Decision Sciences
publishDate 2025
publishDateSort 2025
record_format rss_article
spellingShingle Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
Computer Science
General
Computer Science
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Science
General
Computer Science
Computer Science
General
Computer Science
subject_facet Computer Science
General
Computer Science
title Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
title_auth Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
title_full Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
title_fullStr Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
title_full_unstemmed Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
title_short Quantifying the Digital Divide: A Data-Driven Approach with EFA, Shannon Entropy and Sensitivity Testing
title_sort quantifying the digital divide: a data-driven approach with efa, shannon entropy and sensitivity testing
topic Computer Science
General
Computer Science
url https://sciendo.com/article/10.2478/fcds-2025-0020