Novel Use of Social Media Big Data and Artificial Intelligence for Community Resilience Assessment (CRA) in University Towns

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.

Automated summary

University towns in the 21st century face challenges related to urbanization, growing student population, and inadequate on-campus housing. To ensure resilience and sustainability, these challenges must be identified and addressed. This study utilized artificial intelligence and social media big data (user-generated content on Twitter) to conduct remote community resilience assessments in six university towns across different continents. By analyzing historical big data and validating the findings through an online expert survey, cultural, social, physical, economic, and institutional challenges were identified. The study demonstrates that artificial intelligence offers a convenient, cost-effective, and accurate approach to evaluating community resilience in urban areas and contributes to the understanding of research in the new normal by proving the feasibility of remote longitudinal studies.