Dataset Information

Comparing online travel review platforms as destination image information agents

ABSTRACT: Online travel reviews have been extensively used as an important data source in tourism research. Typically, data for online travel review research is collected only from one platform. However, drawing definite conclusions based on single platform analyses may thus produce biases and lead to erroneous conclusions and decisions. Therefore, this research verifies whether or not there are discrepancies and commonalities between different travel review platforms. In this study, five native Chinese travel review platforms were selected: Ctrip; Qyer; Mafengwo; Tuniu; and Qunar. Using a mixed content analysis method, the destination image of Finland was extracted from 10,197 travel reviews in Simplified Chinese as the destination image is a popular topic in online review research. Results show Finland’s destination image representation varies between Chinese travel review platforms. This discrepancy is especially prominent in the dimension of functional and mixed functional-psychological destination attributes. Significant theoretical contributions and managerial implications for the analysis of online travel reviews and destination image research are discussed.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40558-021-00201-w.

SUBMITTER: Guo X

PROVIDER: S-EPMC8062146 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundThe exponential increase in health-related online platforms has made the Internet one of the main sources of health information globally. The quality of health contents disseminated on the Internet has been a central focus for many researchers. To date, however, few comparative content analyses of pro- and anti-vaccination websites have been conducted, and none of them compared the quality of information. The main objective of this study was therefore to bring new evidence on this aspect by comparing the quality of pro- and anti-vaccination online sources.MethodsBased on past literature and health information quality evaluation initiatives, a 40-categories assessment tool (Online Vaccination Information Quality Codebook) was developed and used to code a sample of 1093 webpages retrieved via Google and two filtered versions of the same search engine. The categories investigated were grouped into four main quality dimensions: web-related design quality criteria (10 categories), health-specific design quality criteria (3 categories), health related content attributes (12 categories) and vaccination-specific content attributes (15 categories). Data analysis comprised frequency counts, cross tabulations, Pearson's chi-square, and other inferential indicators.ResultsThe final sample included 514 webpages in favor of vaccination, 471 against, and 108 neutral. Generally, webpages holding a favorable view toward vaccination presented more quality indicators compared to both neutral and anti-vaccination pages. However, some notable exceptions to this rule were observed. In particular, no differences were found between pro- and anti-vaccination webpages as regards vaccination-specific content attributes.ConclusionsOur analyses showed that the overall quality of pro-vaccination webpages is superior to anti-vaccination online sources. The developed coding scheme was proven to be a helpful and reliable tool to judge the quality of vaccination-related webpages. Based on the results, we advance recommendations for online health information providers as well as directions for future research in this field.

Dataset Information

Comparing online travel review platforms as destination image information agents

Supplementary Information

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