Recommendation agents and information sharing through social media for coronavirus outbreak.

Autor: Nilashi M; Informatics Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam.; Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City, Vietnam.; School of Computer Engineering, Iran University of Science and Technology, Iran., Asadi S; Centre of Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia., Minaei-Bidgoli B; School of Computer Engineering, Iran University of Science and Technology, Iran., Ali Abumalloh R; Computer Department, Community College, Imam Abdulrahman Bin Faisal University, P.O. Box. 1982, Dammam, Saudi Arabia., Samad S; Department of Business Administration, College of Business and Administration, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia., Ghabban F; College of Computer Science and Engineering, Information System Department, Taibah University, Saudi Arabia., Ahani A; Department of Business Strategy and Innovation, Griffith Business School, Griffith University, Brisbane, Australia.
Jazyk: angličtina
Zdroj: Telematics and informatics [Telemat Inform] 2021 Aug; Vol. 61, pp. 101597. Date of Electronic Publication: 2021 Mar 09.
DOI: 10.1016/j.tele.2021.101597
Abstrakt: The novel outbreak of coronavirus disease (COVID-19) was an unexpected event for tourism in the world as well as tourism in the Netherlands. In this situation, the travelers' decision-making for tourism destinations was heavily affected by this global event. Social media usage has played an essential role in travelers' decision-making and increased the awareness of travel-related risks from the COVID-19 outbreak. Online consumer media for the outbreak of COVID-19 has been a crucial source of information for travelers. In the current situation, tourists are using electronic word of mouth (eWOM) more and more for travel planning. Opinions provided by peer travelers for the outbreak of COVID-19 tend to reduce the possibility of poor decisions. Nevertheless, the increasing number of reviews per experience makes reading all feedback hard to make an informed decision. Accordingly, recommendation agents developed by machine learning techniques can be effective in the analysis of such social big data for the identification of useful patterns from the data, knowledge discovery, and real-time service recommendations. The current research aims to adopt a framework for the recommendation agents through topic modeling to uncover the most important dimensions of COVID-19 reviews in the Netherland forums in TripAdvisor. This study demonstrates how social networking websites and online reviews can be effective in unexpected events for travelers' decision making. We conclude with the implications of our study for future research and practice.
Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(© 2021 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: