Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105326
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Building and Real Estate | - |
dc.creator | Abdul-Rahman, M | - |
dc.creator | Adegoriola, MI | - |
dc.creator | McWilson, WK | - |
dc.creator | Soyinka, O | - |
dc.creator | Adenle, YA | - |
dc.date.accessioned | 2024-04-12T06:51:41Z | - |
dc.date.available | 2024-04-12T06:51:41Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/105326 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Abdul-Rahman M, Adegoriola MI, McWilson WK, Soyinka O, Adenle YA. Novel Use of Social Media Big Data and Artificial Intelligence for Community Resilience Assessment (CRA) in University Towns. Sustainability. 2023; 15(2):1295 is available at https://doi.org/10.3390/su15021295. | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Natural language processing | en_US |
dc.subject | Social media | en_US |
dc.subject | Studentification | en_US |
dc.subject | Sustainability | en_US |
dc.subject | Text mining | en_US |
dc.title | Novel use of social media big data and artificial intelligence for Community Resilience Assessment (CRA) in university towns | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 15 | - |
dc.identifier.issue | 2 | - |
dc.identifier.doi | 10.3390/su15021295 | - |
dcterms.abstract | University towns face many challenges in the 21st century due to urbanization, increased student population, and higher educational institutions’ inability to house all their students on-campus. For university towns to be resilient and sustainable, the challenges facing them must be assessed and addressed. To carry out community resilience assessments, this study adopted a novel methodological framework to harness the power of artificial intelligence and social media big data (user-generated content on Twitter) to carry out remote studies in six university towns on six continents using Text Mining, Machine Learning, and Natural Language Processing. Cultural, social, physical, economic, and institutional and governance community challenges were identified and analyzed from the historical big data and validated using an online expert survey. This study gives a global overview of the challenges university towns experience due to studentification and shows that artificial intelligence can provide an easy, cheap, and more accurate way of conducting community resilience assessments in urban communities. The study also contributes to knowledge of research in the new normal by proving that longitudinal studies can be completed remotely. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Sustainability, Feb. 2023, v. 15, no. 2, 1295 | - |
dcterms.isPartOf | Sustainability | - |
dcterms.issued | 2023-02 | - |
dc.identifier.scopus | 2-s2.0-85146728411 | - |
dc.identifier.eissn | 2071-1050 | - |
dc.identifier.artn | 1295 | - |
dc.description.validate | 202403 bcvc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Research Institute for Sustainable Development (RISUD) and the Department of Building and Real Estate of the Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
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File | Description | Size | Format | |
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sustainability-15-01295.pdf | 5.32 MB | Adobe PDF | View/Open |
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