Information and Communication Technologies in Tourism 2021 2021
DOI: 10.1007/978-3-030-65785-7_21
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Tourist Experiences at Overcrowded Attractions: A Text Analytics Approach

Abstract: As a result of travel activities, overtourism has become a global issue. Even after the COVID-19 pandemic, the topic of overtourism would benefit localized overcrowding as a new occurrence in the tourism industry. Since there is no specific measurement to evaluate tourist experiences at crowded attractions, this study aims to explore the perception and feelings of tourists when they visit popular and crowded attractions through topic modeling and sentiment analysis based on TripAdvisor online reviews as of the… Show more

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Cited by 16 publications
(6 citation statements)
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“…We have also shown that purpose-built AR experiences can be effective with very little in the way of a physical set (see Figure 4). Pragmatically, this means that tourism managers can host engaging experiences without the need for visitors to gather around delicate artifacts, thereby reducing overcrowding, which has been associated with several negative outcomes (e.g., safety concerns; Yu & Egger, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…We have also shown that purpose-built AR experiences can be effective with very little in the way of a physical set (see Figure 4). Pragmatically, this means that tourism managers can host engaging experiences without the need for visitors to gather around delicate artifacts, thereby reducing overcrowding, which has been associated with several negative outcomes (e.g., safety concerns; Yu & Egger, 2021).…”
Section: Discussionmentioning
confidence: 99%
“…Meanwhile, in many cases, insufficient information exists in tourism concerning the necessary steps of data pre-processing and how hyperparameters are defined. For instance, in some recent tourism studies, the default hyperparameters were used, and the number of topics was defined without estimating these parameters (Celuch, 2021; Yu and Egger, 2021). Consequently, non-ideal results might have been reported as a successful topic extraction.…”
Section: Discussionmentioning
confidence: 99%
“…Xu et al [9] constructed an extended sentiment dictionary, including basic sentiment words, the field sentiment words and polysemy sentiment words, and obtained the sentiment polarity of the text by using the extended sentiment dictionary and the designed sentiment scoring rules. Yu and Egger [10] used the VADER algorithm, a sentiment-scoring method for text based on sentiment lexicons and rules, to explore how tourists feel about safety, service, queues, etc. when visiting popular and crowded attractions.…”
Section: A Sentiment Analysis Based On Sentiment Dictionarymentioning
confidence: 99%