
This chapter presents and discusses the implications of current approaches to understand practices of users accessing tourism-related online content, especially when it comes to their understanding and interpretation of main contents and sentiments being expressed in the resources they navigate. The Eye-Tracking technique has been implemented to reach such goal, integrating results from previous research conducted by the authors (Marchiori and Cantoni, Information and communication technologies in tourism 2015, Springer, Cham; Cantoni et al., Design, user experience, and usability: understanding users and contexts, Springer, Cham, 2017). The eye-tracking technique is used to explore the match between users’ actual navigation on webpages and their interpretation of the topics covered by such online resources. Results suggest that a multisource approach/data triangulation helps to reduce possible biases that may occur if only one approach is adopted both in online content analysis as well as in online consumer behavior investigation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
