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dc.contributor.authorWeismayer, Christian
dc.contributor.authorPezenka, Ilona
dc.contributor.authorLoibl, Wilhelm
dc.date.accessioned2019-11-06T10:21:40Z
dc.date.available2019-11-06T10:21:40Z
dc.identifier.citationWeismayer, C., Pezenka, I., & Loibl, W. (2016). Automated Hyperlink Text Analysis of City Websites: Projected Image Representation on the Web. In Information and Communication Technologies in Tourism 2016 (pp. 59-72). Springer, Cham.en_US
dc.identifier.isbn9783319282312en_US
dc.identifier.urihttp://hdl.handle.net/10034/622797
dc.descriptionThe final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-28231-2_5en_US
dc.description.abstractThe objective of this study is to identify the image representations of 75 European cities on the Web. As an effective image positioning strategy will result in successful differentiation from competitors, it is crucial for tourism destinations to regularly examine their image. This study focuses on the supply-side of destination image formation and is therefore concerned with analysing the projected destination image. Hyperlink text of DMO websites was collected automatically by a crawler. The text was then edited and filtered. Latent semantic dimensions were generated by applying PCA. A hierarchical cluster approach revealed different groups of hyperlink terms. Finally, the co-occurrence of terms and cities was displayed in a joint-map indicating which groups of hyperlink terms are over- or underrepresented for each of the cities. This information permits conclusions regarding the projected image of the cities.en_US
dc.publisherSpringer International Publishing Switzerlanden_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.subjectDestination imageen_US
dc.subjectDMO websiteen_US
dc.subjectEuropean city destinationsen_US
dc.titleAutomated Hyperlink Text Analysis of City Websites: Projected Image Representation on the Weben_US
dc.typeConference Proceedingen_US
or.grant.openaccessYesen_US
rioxxterms.fundernoneen_US
rioxxterms.identifier.projectnoneen_US
rioxxterms.versionAMen_US
rioxxterms.versionofrecord10.1007/978-3-319-28231-2_5en_US
rioxxterms.licenseref.startdate2216-01-23
refterms.dateFCD2019-10-25T09:21:18Z
refterms.versionFCDAM
rioxxterms.publicationdate2016
dc.dateAccepted2016
dc.date.deposited2019-11-06en_US


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