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Social Vulnerability to COVID-19 -

Social Vulnerability to COVID-19

Impacts of Technology Adoption and Information Behavior
Buch | Hardcover
IX, 136 Seiten
2023 | 1st ed. 2023
Springer International Publishing (Verlag)
978-3-031-06896-6 (ISBN)
CHF 89,85 inkl. MwSt
This book provides an overview of the impact of the pandemic in China and the USA and presents a research agenda for use, access, and adoption of information and communication technologies (ICT) in the era of COVID-19.  The global COVID-19 pandemic changed lives overnight and exposed socially vulnerable populations to ever-challenging situations. One significant challenge was the use, access, and adoption of technological resources.  To understand how socially vulnerable populations managed the COVID-19 pandemic and adapt to the new normal, it is important for researchers and practitioners to identify the challenges and understand the perceptions of technologies.  Through various research studies, this edited volume addresses the impact of the global COVID-19 pandemic and the adoption of technologies (from artificial intelligence to telehealth and telecommunications) among some socially vulnerable populations (including children, older adults, COVID-19 patients, and general marginalized populations) in the world.  The information divide faced by socially vulnerable groups is studied as well as the dimension of vulnerabilities and the impacts of specific technologies.

Xiaojun (Jenny) Yuan, Ph.D., is Associate Professor and Director of the Human-Computer Interaction Lab in the College of Emergency Preparedness, Homeland Security, and Cybersecurity at the University at Albany, State University of New York. Her research interests include both human-computer interaction and information retrieval, with the focus on user interface design and evaluation and human information behavior. She has published extensively in journals in information retrieval and human-computer interaction (including the JASIS&T, IP&M, Journal of Documentation, etc.), and conferences in computer science and information science (ACM SIGIR, ACM SIGCHI, ACM CHIIR, ASIS&T, etc.). Dr. Yuan received her Ph.D. from Rutgers University at School of Communication and Information and Ph.D. from the Institute of Computing Technology of Chinese Academy of Sciences. She received her M.S. in Statistics from Rutgers University and M.E. and B.E. in Computer Application from Xi'an University of Science and Technology in China. She serves as committee members and reviewers in various professional conferences such as ASIS&T, iConference, ACM SIGIR, ACM SIGCHI, ACM CHIIR, and ChineseCHI. She serves as Editorial Board member of Aslib Journal of Information Management (AJIM), and Board member of the International Chinese Association of Human-Computer Interaction. She is a member of the Special Interest Group on Information Needs, Seeking, and Use (SIGUSE) of the Association for Information Science and Technology (ASIS&T), Association for Computing Machinery (ACM), and Institute of Electrical and Electronics Engineers (IEEE). Dan Wu, Ph.D., is Professor in the School of Information Management at Wuhan University, Member of the Academic Committee of Wuhan University, and Director of the Human-Computer Interaction and User Behavior Research Center. Her research areas include information organization and retrieval, user information behavior, human-computer interaction, and digital libraries. Her work is published in various journals (including the IP&M, JASIST, etc.). She has presented at several conferences related to information behavior, information retrieval, and digital library (SIGIR, CIKM, CSCW, CHIIR, etc.). Dr. Wu received her Ph.D. from the Peking University in Management. She serves as Editor-in-Chief of Aslib Journal of Information Management and Executive Editor of Data and Information Management. She also serves as a director at large of the ASIS&T. She is a member of the ACM Digital Library Committee, a member of the iSchool Data Science Curriculum Committee, and a member of the JCDL Steering Committee. DeeDee Bennett Gayle, Ph.D. is Associate Professor in the College of Emergency Preparedness, Homeland Security, and Cybersecurity at the University at Albany, State University of New York. She broadly examines the influence and integration of advanced technologies on the practice of emergency management, and for use by vulnerable populations. Her work is published in various journals, and she has presented at several conferences related to emergency management, disability, wireless technology, and future studies. Dr. Bennett Gayle received her Ph.D. from Oklahoma State University in Fire and Emergency Management. She has a unique academic background having received both her M.S. in Public Policy and B.S. in Electrical Engineering from the Georgia Institute of Technology. She is Advisory Board Member for the Institute for Diversity and Inclusion in Emergency Management (I-DIEM), a member of the Social Science Extreme Events Reconnaissance (SSEER) and Interdisciplinary Science Extreme Events Reconnaissance (ISEER), within the NSF-FUNDED CONVERGE initiative.

Introduction.- Technological Innovations in Response to COVID-19: Research Agenda Considering Marginalized Populations.- Adoption of Artificial Intelligence Technologies by Often Marginalized Populations.-  Mining the Health Information Needs of COVID-19 Patients based on Social Q&A Community.- Digital Divide Faced by the Elderly Under the COVID-19 Pandemic.- Difficulties of Vulnerable Groups in Accessing the Public Information Service during COVID-19 Pandemic in China.- Responding to COVID-19: Privacy Implications of the Rapid Adoption of ICTs.- Conclusion. 

Erscheinungsdatum
Reihe/Serie Synthesis Lectures on Information Concepts, Retrieval, and Services
Zusatzinfo IX, 136 p. 19 illus., 14 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 168 x 240 mm
Gewicht 418 g
Themenwelt Informatik Datenbanken Data Warehouse / Data Mining
Mathematik / Informatik Informatik Theorie / Studium
Schlagworte Artificial Intelligence Technologies • Communication technologies • Covid-19 • Information Retrieval • Information Technologies
ISBN-10 3-031-06896-3 / 3031068963
ISBN-13 978-3-031-06896-6 / 9783031068966
Zustand Neuware
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