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Examining destination images from travel blogs: a big data analytical approach using latent Dirichlet allocation

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TLDR
In the big data era, destination images have played an increasingly important role in tourism development as discussed by the authors, however, seldom tourism research has utilised big data analytics to examine destination images.
Abstract
In the big data era, destination images have played an increasingly important role in tourism development. However, seldom tourism research has utilised big data analytics to examine destin...

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Citations
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Destination marketing organizations and destination marketing : a narrative analysis of the literature

TL;DR: In this article, the authors present the first narrative analysis of the areas of research that have developed within the destination marketing field since its commencement in 1973 and address a number of themes including nomenclature and the Destination Marketing Organisation (DMO), the evolution of destination marketing literature, competitiveness as the DMO reason d'etre, and DMO effectiveness.
Journal ArticleDOI

From desktop to destination: User-generated content platforms, co-created online experiences, destination image and satisfaction

TL;DR: In this paper, the authors proposed user-generated platforms as a contributor to the online co-creation process and how this cocreation experience enhances a travel destination's image and, subsequently, impacts on the travel experience.
Journal ArticleDOI

Developing an artificial intelligence framework for online destination image photos identification

TL;DR: An artificial intelligence (AI) framework is developed to identify tourism photos without human interaction and the results indicate that the AI photo identification framework is of great benefit for the understanding of projected destination images and enhancing tourism experiences.
Journal ArticleDOI

Impact of Short Food Videos on the Tourist Destination Image—Take Chengdu as an Example

Yi Li, +3 more
- 20 Aug 2020 - 
TL;DR: This paper is inspiring for city managers and tourism marketers to use TikTok short videos to establish and disseminate food-based city brands and destination images.
Journal ArticleDOI

Traveller-generated destination image: Analysing Flickr photos of 193 countries worldwide

TL;DR: Destination marketing organisations can use a method that utilises a combination of Google Cloud Vision AI's label detection and a topic-modelling algorithm, latent Dirichlet allocation, to identify common destination images and to compare destinations worldwide.
References
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Proceedings Article

Latent Dirichlet Allocation

TL;DR: This paper proposed a generative model for text and other collections of discrete data that generalizes or improves on several previous models including naive Bayes/unigram, mixture of unigrams, and Hof-mann's aspect model, also known as probabilistic latent semantic indexing (pLSI).
Journal ArticleDOI

Finding scientific topics

TL;DR: A generative model for documents is described, introduced by Blei, Ng, and Jordan, and a Markov chain Monte Carlo algorithm is presented for inference in this model, which is used to analyze abstracts from PNAS by using Bayesian model selection to establish the number of topics.
Journal ArticleDOI

A model of destination image formation

TL;DR: A major finding was that a destination image is formed by both stimulus factors and tourists' characteristics, which provides important implications for strategic image management and can aid in designing and implementing marketing programs for creating and enhancing tourism destination images.
Journal ArticleDOI

How destination image and evaluative factors affect behavioral intentions

TL;DR: In this paper, a more integrated tourist behavior model by including destination image and perceived value into the "quality-satisfaction-behavioral intentions" paradigm was proposed, and the structural relationships between all variables with respect to different stages of tourist behaviors were investigated in the study.
Journal ArticleDOI

Factors influencing destination image

TL;DR: In this paper, the authors develop and empirically validate a model which explains the different factors which form the post-visit image of a destination based on a literature review, which will involve analyzing the relationship between the different components of the perceived image and the factors which influence its formation.
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