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1 |
Storytelling approach of the self-reported slow adventure to Tibet: Constructing experience and identity
رویکرد داستان پردازی از ماجراجویی کند گزارش شده خود به تبت: ساخت تجربه و هویت-2020 Most of our travel experiences are stored, recorded, and relived in the form of stories; tourist blogs have emerged
as a modern form of travel story. These stories provide information about exciting moments and memorable
events, which are usually emotional highpoints that can be useful for tourism marketers. Based on the sociological
concept of storytelling, this study investigates which aspects of the slow adventure experience travelers
present in their travel blogs through a rubric elaborated on extant literature. The findings reveal three types of
slow adventure stories, and each type of story relates to a different identity construction. The article concludes
with a discussion of its theoretical contributions in terms of adding to the literature of adventure tourism and
storytelling. In revealing the themes and identities relating to specific slow adventure experiences, it provides
potential practical implications of travel blogs for slow adventure product designers and marketers. Keywords: Adventure tourism | Travel blog | Storytelling | Identity management | Tourist experience |
مقاله انگلیسی |
2 |
What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management
چه چیزی باعث احساس منفی گردشگران درباره مقصد گردشگری میشود ؟ استفاده از متدولوژی استخراج متن ترکیبی به مدیریت مقصد هوشمند-2017 Recently, the Internet has brought a big change in tourists behavior patterns. Travelers not only reserve hotels
and airline tickets online, but also exchange travel information and descriptions of pleasant or unpleasant travel
experiences through online review sites and personal travel blogs. In spite of the increasing use of online
channels, application of online text data has been limited since the volume of the data set is too large to analyze
manually and comprehensively. With recent technological advances in processing big data online, consumer
generated information can be automatically analyzed by artificial intelligence.
As an aspect of smart tourism, this study applied the sentiment analysis method to analyze travelers online re
views of Paris. A total of 19,835 pieces of review data collected from a traveler review site (www.virtualtourist.
com) were processed. All reviews were grouped into 14 categories as follows: overview, restaurants, sightseeing,
hotels, things to do, night life, transportation, shopping, sporting & outdoors, favorites, off the beaten path, what
to pack, tourist traps, warnings and danger, and local customs. Tourists perception about the service in each cat
egory was successfully measured, and as an illustration, we chose “transportation” category that reported rela
tively low level of service quality for post-hoc analysis to reveal why tourists feel negatively about the
transportation service.
Keywords: Smart tourism | Smart destination management | Sentiment analysis | Text mining | User-generated content (UGC) |
مقاله انگلیسی |