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Analyzing public opinions regarding virtual tourism in the context of COVID-19: Unidirectional vs. 360-degree videos

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dc.title Analyzing public opinions regarding virtual tourism in the context of COVID-19: Unidirectional vs. 360-degree videos en
dc.contributor.author Huynh Thai, Hoc
dc.contributor.author Šilhavý, Petr
dc.contributor.author Dey, Sandeep Kumar
dc.contributor.author Hoang, Duc Sinh
dc.contributor.author Prokopová, Zdenka
dc.contributor.author Šilhavý, Radek
dc.relation.ispartof Information (Switzerland)
dc.identifier.issn 2078-2489 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2023
utb.relation.volume 14
utb.relation.issue 1
dc.type article
dc.language.iso en
dc.publisher MDPI
dc.identifier.doi 10.3390/info14010011
dc.relation.uri https://www.mdpi.com/2078-2489/14/1/11
dc.relation.uri https://www.mdpi.com/2078-2489/14/1/11/pdf?version=1672318187
dc.subject virtual tourism en
dc.subject COVID-19 en
dc.subject SentiStrength-SE en
dc.subject SenticNet7 en
dc.subject 360-degrees videos en
dc.subject unidirectional videos en
dc.subject optimal sentiment analyses model en
dc.subject convolutional neural network en
dc.subject random forest en
dc.subject max-voting en
dc.description.abstract Over the last few years, more and more people have been using YouTube videos to experience virtual reality travel. Many individuals utilize comments to voice their ideas or criticize a subject on YouTube. The number of replies to 360-degree and unidirectional videos is enormous and might differ between the two kinds of videos. This presents the problem of efficiently evaluating user opinions with respect to which type of video will be more appealing to viewers, positive comments, or interest. This paper aims to study SentiStrength-SE and SenticNet7 techniques for sentiment analysis. The findings demonstrate that the sentiment analysis obtained from SenticNet7 outperforms that from SentiStrength-SE. It is revealed through the sentiment analysis that sentiment disparity among the viewers of 360-degree and unidirectional videos is low and insignificant. Furthermore, the study shows that unidirectional videos garnered the most traffic during COVID-19 induced global travel bans. The study elaborates on the capacity of unidirectional videos on travel and the implications for industry and academia. The second aim of this paper also employs a Convolutional Neural Network and Random Forest for sentiment analysis of YouTube viewers' comments, where the sentiment analysis output by SenticNet7 is used as actual values. Cross-validation with 10-folds is employed in the proposed models. The findings demonstrate that the max-voting technique outperforms compared with an individual fold. en
utb.faculty Faculty of Applied Informatics
utb.faculty Faculty of Management and Economics
dc.identifier.uri http://hdl.handle.net/10563/1011383
utb.identifier.obdid 43884668
utb.identifier.scopus 2-s2.0-85146754375
utb.identifier.wok 000917600000001
utb.source j-scopus
dc.date.accessioned 2023-02-17T00:08:31Z
dc.date.available 2023-02-17T00:08:31Z
dc.description.sponsorship IGA/CebiaTech/2022/001
dc.description.sponsorship TBU in Zlin [CZ.02.2.69/0.0/19_073/0016941]; Faculty of Applied Informatics, Tomas Bata University in Zlin [IGA/CebiaTech/2022/001]
dc.rights Attribution 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.rights.access openAccess
utb.contributor.internalauthor Huynh Thai, Hoc
utb.contributor.internalauthor Šilhavý, Petr
utb.contributor.internalauthor Dey, Sandeep Kumar
utb.contributor.internalauthor Hoang, Duc Sinh
utb.contributor.internalauthor Prokopová, Zdenka
utb.contributor.internalauthor Šilhavý, Radek
utb.fulltext.dates Received: 6 November 2022 Revised: 15 December 2022 Accepted: 19 December 2022 Published: 26 December 2022
utb.fulltext.sponsorship This project has been financed within OP RDE project Junior grants of TBU in Zlin, reg. No. CZ.02.2.69/0.0/19_073/0016941 was supported by the Faculty of Applied Informatics, Tomas Bata University in Zlin, under Project No.: IGA/CebiaTech/2022/001.
utb.wos.affiliation [Thai, Hoc Huynh; Silhavy, Petr; Prokopova, Zdenka; Silhavy, Radek] Tomas Bata Univ Zlin, Fac Appl Informat, Stranemi 4511, Zlin 76001, Czech Republic; [Thai, Hoc Huynh] Lang Univ, Fac Informat Technol, Sch Engn & Technol, Ho Chi Minh City 700000, Vietnam; [Dey, Sandeep Kumar; Hoang, Sinh Duc] Tomas Bata Univ Zlin, Fac Management & Econ, Zlin 76001, Czech Republic; [Dey, Sandeep Kumar] Czech Math Soc Matemat ustav, CR, v v i, Zitna 609-25, Praha 1 11000, Czech Republic; [Hoang, Sinh Duc] Ho Chi Minh City Univ Foreign Languages Informat T, Dept Econ Finance, Ho Chi Minh City 700000, Vietnam
utb.scopus.affiliation Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, Zlin, 76001, Czech Republic; Faculty of Information Technology, School of Engineering and Technology, Van Lang University, Ho Chi Minh City, 700000, Viet Nam; Faculty of Management and Economics, Tomas Bata University in Zlin, Zlin, 76001, Czech Republic; Czech Mathematical Society Matematický ústav AV ČR, v.v.i., Žitná 609/25, Praha 1, 11000, Czech Republic; Department of Economics Finance, Ho Chi Minh City University of Foreign Languages Information Technology, Ho Chi Minh City, 700000, Viet Nam
utb.fulltext.projects CZ.02.2.69/0.0/19_073/0016941
utb.fulltext.projects IGA/CebiaTech/2022/001
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Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International